50+ Python Jobs in Delhi, NCR and Gurgaon | Python Job openings in Delhi, NCR and Gurgaon

Hiring for Lead Python Developer

Exp : 7+ yrs

Edu : BE/B.Tech

Work Location : Bengaluru / Gurugram Hybrid

Skills :

Strong expertise in Python programming. 

Experience with frameworks such as: Django Flask FastAPI 

Strong understanding of: REST APIs Microservices Architecture OOPs Concepts Design Patterns 

Experience with databases: PostgreSQL MySQL MongoDB Redis 

Hands-on experience with: Docker Kubernetes CI/CD Pipelines Git/GitHub/GitLab 

Cloud platform experience: AWS / Azure / GCP 

Knowledge of message brokers: Kafka / RabbitMQ 

Experience with unit testing and automation frameworks. 

Leadership Skills Strong team handling and mentoring experience. 

Ability to drive technical discussions and architecture decisions. 

Excellent stakeholder management and communication skills. 

Experience managing Agile/Scrum teams. 

Preferred Qualifications Bachelor’s/Master’s degree in Computer Science or related field.

 Experience in large-scale enterprise applications.

Exposure to AI/ML integrations is an added advantage. Certifications in cloud or Python technologies are preferred.

Role overview:

We are hiring one Senior Backend Engineer to take end-to-end ownership of our serverless backend — a hands-on IC role for someone both technically excellent and comfortable being one of the few people the entire backend depends on. You'll own the services across several Node.js and Python repositories, work directly with the founders and product team, and set the technical bar for reliability, security, and performance.

Key responsibilities

• Design, build, and operate AWS Lambda services across our HCM/workforce, project-management, commercial/revenue, permissions, and document domains — each comprising dozens of functions.
• Own the multi-tenant PostgreSQL data layer — schema design, query performance, and the permission/relationship model — end to end.
• Maintain and evolve the request path — API Gateway → custom Lambda authorizer → VPC-bound Lambda → private databases — including the runtime IAM/credential model that scopes every request.
• Safeguard tenant isolation and security across a per-company Cognito authentication model.
• Build and maintain integrations with external construction data environments (Asite, Autodesk Construction Cloud), including large-scale document synchronization.
• Optimize performance and reliability to keep latency-sensitive endpoints well within platform limits under growing load.
• Raise the engineering bar — testing, observability, CI/CD, and modernization of legacy components.
• Debug and resolve production incidents to root cause, and put safeguards in place so they don't recur.
• Document decisions and designs and collaborate with the frontend (Angular) and product teams.

Challenges you'll solve.

We prefer to be candid — these are the problems that make this role genuinely interesting:

Latency under a hard ceiling

API Gateway terminates any request beyond ~29 seconds regardless of the Lambda's own timeout — yet much of our value comes from heavy cross-project reporting. You'll keep p95 latency within budget through set-based SQL, pagination, streaming, and asynchronous processing.

Least-privilege, per-request security

A shared custom authorizer mints short-lived, request-scoped credentials via sts:AssumeRole under a strict 2,048-character inline session-policy limit. You'll design permission models that stay within that budget and reason about IAM precisely.

Graph-shaped data, relational store

The permission and relationship model is inherently graph-like, but lives in PostgreSQL — you'll model it with recursive queries, careful indexing, and set-based traversal rather than reaching for a separate graph engine.

Watertight multi-tenancy

One Cognito pool per company and tenant-scoped access throughout — isolation is a first-order concern.

VPC-bound serverless

Lambdas run inside a VPC to reach private databases; you'll manage cold starts, connection lifecycles, and pool limits.

Resilient external integrations

Syncing large document sets from third-party APIs (including SOAP/XML) demands backpressure, deduplication, retries, and graceful partial-failure handling.

Compute-heavy workloads

Server-side PDF generation, image processing, and multi-currency handling within Lambda's memory and time constraints.

The stack.

Runtime — Node.js, Python, AWS Lambda

AWS services — -1 API Gateway, Lambda, Cognito, STS / IAM, Secrets Manager, S3 CloudWatch, VPC, EC2

Infrastructure & CI/CD- AWS SAM, CodePipeline → CodeBuild Shared Data —PostgreSQL

Qualifications.

• 5+ years building and operating production backend systems.
• Deep expertise in Node.js and JavaScript — the asynchronous model, event loop, and memory behavior — plus solid working proficiency in Python and its production behavior.
• Strong hands-on AWS experience, ideally serverless (Lambda, API Gateway, IAM/STS, VPC, Secrets Manager, CloudWatch) — able to reason about IAM policies, not just apply them.
• Advanced SQL and relational data modeling — set-based query design and a working understanding of why N+1 patterns cause production issues.
• Proven production-debugging ability — root-cause analysis in distributed systems from logs and first principles.
• Strong ownership, sound judgment, and clear written communication — able to make good decisions with incomplete information and explain trade-offs to non-engineers.

Interview Process:

Introductory call-Mutual fit and role overview.

Technical deep-dive- A walkthrough of a challenging production problem you have owned.

Practical exercise -A realistic backend task, or a walkthrough of your own representative code.

System design- Collaborative design on a real scenario.

Final conversation- Values, ownership, compensation, and offer.

Job Title: Frontend Developer

Location: Arjan Garh, MG Road (Delhi)

Job Type: Full-time, On site

**IMMEDIATE JOINERS REQUIRED**

About Us

Our Aim is to develop ‘More Data, More Opportunities’. We take pride in building cutting-edge AI solutions to help financial institutions mitigate risk and generate comprehensive data. We are looking for a talented Frontend Developer to join our dynamic team and contribute to that which makes a real impact.

Job Summary

We are looking for a creative and technically skilled Front-End Developer who can seamlessly blend UI/UX design principles with robust coding practices. The ideal candidate will collaborate with our development team to create visually appealing and user-friendly web applications.

Key Responsibilities

• UI/UX Implementation: Convert design prototypes (e.g., from Figma, Sketch) into pixel-perfect HTML/CSS. Ensure the design is responsive using CSS media queries, Grid, and Flexbox.
• Design and implement RESTful APIs or GraphQL endpoints using backend stacks such as Node.js (Express/Nest), Python (Django/Flask), Java (Spring Boot)
• Feature Development: Develop new user-facing features using HTML, CSS, and JavaScript. Build reusable code and libraries for future use.
• Cross-Functional Collaboration: Work closely with back-end developers to integrate UI components with server-side logic.
• Version Control: Use version control systems like Git to manage and review reusable, clean, and efficient code.
• Responsive Design: Develop websites that work across different screen sizes, from mobile phones to large desktops, by using a mobile-first approach and CSS methodologies.
• Testing and Debugging: Identify and resolve functionality issues to ensure smooth user experiences across various browsers and devices.
• Continuous Learning: Stay updated with emerging front-end technologies, best practices, and industry trends.

Qualifications

• Education: Bachelor's degree in Computer Science, Web Development, or a related field.

Required Skills and Experience:

• Minimum 2 years of software development experience—emphasis on frontend, but ideally exposure across full-stack development.
• Proficiency in HTML5, CSS3, and JavaScript.
• Experience with modern front-end and back end frameworks.
• Familiarity with version control systems such as Git.
• Familiarity with design tools such as Figma, Sketch, or Adobe XD.
• Knowledge of responsive design and cross-browser compatibility issues.

Soft Skills:

• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.
• Ability to work in a collaborative environment and meet deadlines.

About US:-

We turn customer challenges into growth opportunities.

Material is a global strategy partner to the world’s most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.

We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve.

Srijan, a Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners.

Job Description: Sr. Full Stack Engineer (Python, JavaScript & AI Engineering) – 7-8 years 

Role Summary 

We are seeking an experienced Sr. Engineer/Technical Lead with strong expertise in Python, JavaScript/TypeScript, and AI-native application development. The ideal candidate will build scalable cloud applications, architect intelligent systems powered by Large Language Models (LLMs), drive engineering excellence, and help teams adopt modern AI-assisted development practices. This is a hands-on leadership role combining software engineering, AI integration, and technical mentorship. 

Key Responsibilities 

• Design, develop, and maintain scalable applications using Python and JavaScript/TypeScript. 
• Build APIs, microservices, and event-driven cloud-native solutions. 
• Design and implement AI-enabled features using LLMs, RAG, structured outputs, and tool integrations. 
• Build and maintain agentic workflows for business automation and developer productivity. 
• Leverage AI coding assistants and code agents to improve software delivery and engineering efficiency. 
• Integrate enterprise services including authentication, SSO, authorization, and internal platforms. 
• Collaborate with platform teams to deploy and operate applications on AWS or Azure. 
• Drive engineering best practices including CI/CD, testing, observability, code reviews, and secure development. 
• Document architectures, APIs, AI workflows, and key technical decisions. 
• Mentor engineers and help teams adopt modern AI-first development practices. 

Required Skills 

• Strong hands-on experience building production applications with Python. 
• Good experience with JavaScript or TypeScript and modern application architectures. 
• Experience designing REST APIs, microservices, and distributed systems. 
• Practical understanding of LLMs, prompt engineering, RAG, embeddings, vector search, and AI application patterns. 
• Experience integrating commercial or open-source AI models into production systems. 
• Hands-on experience using AI coding assistants and code agents to accelerate development. 
• Understanding of agent orchestration concepts and Model Context Protocol (MCP). 
• Experience with AWS or Azure cloud platforms. 
• Experience with CI/CD, automated testing, code quality, and application observability. 
• Strong communication, documentation, and technical leadership skills. 

Good-to-Have Skills 

• Experience with AI orchestration frameworks such as LangGraph, CrewAI, Semantic Kernel, or similar. 
• Knowledge of FastAPI, Node.js, React, or Next.js. 
• Experience with containers and Kubernetes. 
• Exposure to AI evaluation, guardrails, and production monitoring. 
• Experience mentoring teams and driving AI adoption across engineering organizations. 

Byteridge is seeking a Business Intelligence Solutions engineer to drive

transformative analytics and AI-powered insights for our strategic customers across India. You will lead

complex deployments of Amazon QuickSuite and related AWS analytics services, working directly with

customers to accelerate their data-driven transformation.

This role combines deep technical expertise in business intelligence, data integration, and AI automation to deliver production-ready solutions that unlock the full potential of customer data across multi-cloud environments.

What You'll Do

Solution Architecture & Deployment

• Lead end-to-end deployments of Amazon QuickSuite, QuickSight, and AWS analytics solutions forstrategic customers

• Design and implement comprehensive BI architectures that integrate with diverse data sourcesacross multi-cloud environments

• Develop custom connectors, APIs, and MCP (Model Context Protocol) integrations to extendplatform capabilities

• Configure and optimize Agents, Spaces, Topics, and Dashboards for customer-specific use cases

Technical Development & Integration

• Build custom connectors and integrations to connect QuickSuite with enterprise data sources

• Develop API-based solutions and automation workflows to streamline BI operations

• Implement data pipelines connecting multi-cloud data sources (AWS, Azure, GCP) to analyticsplatforms

• Create reusable templates, accelerators, and best practices for rapid deployment

Customer Engagement & Enablement

• Partner with customer teams to understand business requirements and translate them into

technical solutions

• Provide technical guidance on dashboard design, data modeling, and visualization best practices

• Train customer teams on QuickSuite capabilities, agent configuration, and self-service analytics

• Identify expansion opportunities and drive adoption of advanced analytics features

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent practical

experience

• 4-6 years of experience in business intelligence, data analytics, or technical consulting roles

• Strong programming skills in Python, JavaScript, SQL, or similar languages

• Experience with BI platforms, data visualization, and analytics solution deployment

Technical Expertise (High-Level Alignment)

• Proficiency with business intelligence and data visualization tools (QuickSight, Tableau, Power BI, or

similar)

• Experience with API development, REST services, and integration patterns

• Understanding of data modeling, ETL/ELT processes, and data warehouse concepts

• Familiarity with AWS analytics services (QuickSight, Athena, Glue, Redshift) or equivalent platforms

Preferred Experience

• Hands-on experience with Amazon QuickSuite or similar AI-powered analytics platforms

• Knowledge of MCP (Model Context Protocol) and custom connector development

• Experience configuring AI agents, knowledge bases, and automated workflows

• Background working with multi-cloud data sources and hybrid architectures

• Understanding of data governance, security, and compliance requirements

Essential Attributes

• Excellent problem-solving skills with ability to navigate ambiguous requirements

• Strong communication skills to engage with technical and business stakeholders

• Ability to manage multiple customer engagements and prioritize effectively

• Customer-focused mindset with commitment to delivering measurable business outcomes

Byteridge is seeking a Rapid Prototyping Engineer specializing in AI Infrastructure & Optimization to work with our most strategic customers on deploying, fine-tuning, and optimizing large language models at scale. You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

Strong Python Backend Engineer Profile with hands-on GenAI capabilities

Mandatory (Experience 1) – Must have 3+ years of experience in application development using Python (Django) with atleast 6 months of hands on experience building GenAI applications in production

Mandatory (Tech skill 1) – Must have strong proficiency in Python with a backend framework (Django, Flask or FastAPI) and developing/consuming RESTful APIs.

Mandatory (Tech skill 2) – Must have hands-on experience integrating LLMs (OpenAI GPT-4, Claude, Llama or similar) into production and orchestrating LLM workflows (LangGraph, LangChain)

Mandatory (Tech skill 3) – Must have experience building RAG pipelines using vector databases such as Pinecone or PGVector.

Mandatory (Tech skill 4) – Must have experience with relational databases (PostgreSQL, MySQL) and writing efficient, scalable queries.

Mandatory (Tech skill 5) – Must have a good understanding of software design principles, code modularity and version control (Git).

Mandatory (Education) – Must have a full-time B.E./B.Tech degree, with a minimum of 60% throughout (10th, 12th and B.E./B.Tech). Only B.E./B.Tech is considered; however, the 60% benchmark can be relaxed for candidates with strong technical skills (Kindly mention in resume)

Mandatory (Communication) – Must have good communication skills in both English and Hindi.

Mandatory (Company): IT services/IT consulting

Hands-on experience with PySpark and DataBricks is a must.

Strong experience in Python is a must.

Strong experience with relational (PostgreSQL, MySQL, etc.) and/or NoSQL databases (MongoDB, etc.)

Working experience on streaming services like Kafka, AWS SQS, etc.

Basic understanding of modern deployment solutions such as Docker, Kubernetes and similar container based deployment solutions.

Experience with Linux/Unix Operating system & comfortable with command line. ?

Experience with modern software engineering workflows and tools (e.g. Agile, JIRA, Git, CI/CD (Github actions), Amazon Web Services, ELK, APM).

Experience with Agile development lifecycle.

Job Title : Data Engineer – Databricks

Experience : 6+ Years

Location : Noida / Hyderabad / Chennai / Pune / Bengaluru (Hybrid)

Shift : IST (Normal Shift)

Job Summary :

We are seeking an experienced Data Engineer with strong expertise in Databricks, Snowflake, Python, and Spark to build and optimize scalable data pipelines and support AI/ML model deployments. The ideal candidate should have experience working with cloud-based data platforms and preferably possess exposure to the Healthcare domain.

Required Skills :

• Databricks (Preferred)
• Snowflake
• Python
• Apache Spark
• SQL
• Azure Cloud
• Kubernetes
• Apache Airflow
• GitHub & CI/CD Pipelines
• AI/ML Model Deployment
• Data Analytics

Preferred :

• Experience in the Healthcare domain.
• Strong understanding of scalable data engineering architectures and best practices.

Hands-on experience in developing Restful APIs and Web Services.

Knowledge of Django, FastAPI (or any other established Python web frameworks) would be a plus.

Knowledge of Angular or React or similar technologies would be an added advantage.

Strong experience with relational (PostgreSQL, MySQL) and/or NoSQL databases.

Experience working with Linux/Unix Operating system & comfortable with command line.

Experience with modern software engineering workflows and tools (e.g. Agile, JIRA, Git, CI/CD, Amazon Web Services, Observability and Monitoring tools like ELK, Datadog, NewRelic, etc.).

Extremely passionate about code reviews, engineering best practices and mentoring/coaching the developers to make them successful.

Excellent understanding of feature estimation and ability to communicate issues and risks that may impact timelines, budget, or resources.

Experience with Agile development lifecycle

Job description:

Interview Venue: H-28, ARV Park, Sector 63, Noida, Uttar Pradesh 201301

Job location: Noida

Experience: 1-2 years

Education: B.Tech or MCA

The procedure for the interview will be as follows:

• 1st Round - Machine Round
• 2nd Round- Communication Round
• 3rd Round – Assignment Round
• 4th Round - HR Round

Job Description:

• Profile: AI/ML Engineer
• Experience: 1-2 yrs
• Qualification : B.Tech/MCA
• Working Days: 5
• Job Nature: Permanent

Roles And Responsibilities:

1) Python Proficiency and API Integration:

Demonstrate strong proficiency in Python programming language.

Design and implement scalable, efficient, and maintainable code for machine learning applications.

Integrate machine learning models with APIs to facilitate seamless communication between different software components.

2) Machine Learning Model Deployment, Training, and Performance:

Develop and deploy machine learning models for real-world applications.

Conduct model training, optimization, and performance evaluation.

Collaborate with cross-functional teams to ensure the successful integration of machine learning solutions into production systems.

3) Large Language Model Understanding and Integration:

Possess a deep understanding of large language models (LLMs) and their applications.

Integrate LLMs into existing systems and workflows to enhance natural language processing capabilities.

Stay abreast of the latest advancements in large language models and contribute insights to the team.

4) Langchain and RAG-Based Systems (e.g., LLamaindex):

Familiarity with Langchain and RAG-based systems, such as LLamaindex, will be a significant advantage.

Work on the design and implementation of systems that leverage Langchain and RAG-based approaches for enhanced performance and functionality.

5) LLM Integration with Vector Databases (e.g., Pinecone):

Experience in integrating large language models with vector databases, such as Pinecone, for efficient storage and retrieval of information.

Optimize the integration of LLMs with vector databases to ensure high-performance and low-latency interactions.

6) Natural Language Processing (NLP):

Expertise in NLP techniques such as tokenization, named entity recognition, sentiment analysis, and language translation.

Experience with NLP libraries and frameworks like NLTK, SpaCy, Hugging Face Transformers

7) Computer Vision:

Proficiency in computer vision tasks such as image classification, object detection, segmentation, and image generation.

Experience with computer vision libraries like OpenCV, PIL, and frameworks like TensorFlow, PyTorch, and Keras.

8) Deep Learning:

Strong understanding of deep learning concepts and architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

Proficiency in using deep learning frameworks like TensorFlow, PyTorch, and Keras.

Experience with model optimization, hyperparameter tuning, and transfer learning.

9) Data Manipulation:

Strong skills in data manipulation and analysis using libraries like Pandas, NumPy, and SciPy.

Proficiency in data cleaning, preprocessing, and augmentation techniques.

Perks&Benefits:

• Employees & Family Health Insurance, EPF & ESIC.
• Free late-night meal facility.
• Innumerable in house & outdoor party.
• Various compensations & bonuses.
• No dress Code.
• Festival Celebration.
• Employees' B'day celebration.

Job Title : Senior Software Engineer (Full Stack Capability)

Experience : 4+ Years

Location : West Patel Nagar, New Delhi

Employment Type : Full-Time

About the Role :

We are looking for a highly skilled Senior Software Engineer with 4+ years of experience in designing, developing, and maintaining scalable web applications. The ideal candidate should have strong backend expertise in Java, Python and Node.js while also being capable of handling frontend development when required.

This role requires excellent problem-solving abilities, ownership mindset, and strong communication skills to collaborate effectively with cross-functional teams and stakeholders.

Key Responsibilities :

• Design, develop, and maintain robust backend applications using Java and Node.js.
• Build and consume RESTful APIs and microservices.
• Develop scalable, secure, and high-performance applications.
• Work with frontend technologies to build and enhance user-facing features.
• Collaborate with product managers, designers, and other developers to deliver business requirements.
• Optimize application performance, troubleshoot issues, and implement best practices.
• Write clean, maintainable, and well-documented code.
• Participate in code reviews and contribute to technical discussions.
• Manage database design, optimization, and integrations.
• Ensure application security, scalability, and reliability.

Required Skills & Qualifications :

• 4+ years of professional software development experience.
• Strong hands-on experience with Java, Spring Boot, and related backend frameworks.
• Strong experience with Node.js, Express.js, and API development.
• Good understanding of Microservices Architecture.
• Experience with MySQL, PostgreSQL, or MongoDB.
• Knowledge of Redis, caching mechanisms, and message queues is a plus.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience with version control systems like Git.
• Understanding of CI/CD pipelines and deployment processes.

Frontend Requirements :

• Ability to work on frontend development when required.
• Experience with React.js, JavaScript, TypeScript, HTML5, and CSS3.
• Understanding of responsive design and modern UI development practices.

Soft Skills :

• Excellent verbal and written communication skills.
• Strong stakeholder management and client interaction abilities.
• Ability to work independently and take ownership of projects.
• Strong analytical and problem-solving skills.
• Team player with a collaborative mindset.

Preferred Qualifications :

• Experience working in product-based or fast-paced startup environments.
• Knowledge of Docker, Kubernetes, and DevOps practices.
• Experience with Agile/Scrum methodologies.

Job Title: Engineering Manager

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Role Overview

As an Engineering Manager at Timble AI, you will manage, mentor, and scale our core engineering teams (including Backend, Frontend, and AI/ML divisions). You will remain highly technical, contributing to architecture decisions and system design, while taking full ownership of project delivery timelines, agile sprints, and team performance metrics.

Key Responsibilities

1. People Leadership & Mentorship: Manage and grow a cross-functional team of software engineers (SDE-1 to SDE-3). Conduct regular 1-on-1s, drive career growth paths, and foster an innovative, high-ownership engineering culture.
2. Delivery & Agile Project Management: Own the engineering sprint cycles. Work closely with Product Managers to break down roadmaps into execution goals, manage dependencies, and ensure high-velocity, predictable delivery.
3. System Design & Architecture: Provide technical governance and direction. Collaborate on core system architecture, design reviews, and ensure codebases remain clean, scalable, and modular.
4.  Engineering Excellence: Define and monitor key performance indicators (KPIs) for the engineering team, including code quality, test coverage, uptime, and system performance.
5. Hiring & Scaling: Actively partner with the talent acquisition team to identify, interview, and onboard top-tier engineering talent to help build our core verticals.

Required Skills & Qualifications

1. Experience: 5+ years of core software engineering experience, with at least 1–2 years of experience in an engineering management, tech lead, or team leadership role.
2. Technical Roots: Strong foundational background in backend systems, distributed architectures, or AI integration. Prior hands-on experience with Python/Django ecosystems, microservices, cloud infra (AWS/GCP), or heavy automation systems is highly valued.
3. Agile Mastery: Deep familiarity with Agile/Scrum development methodologies, sprint planning tools, and CI/CD pipelines.
4.  Communication: Exceptional interpersonal and cross-functional communication skills, with a track record of translating complex technical visions into clear execution steps.
5.  Education: B.Tech / M.Tech in Computer Science, Information Technology, or a related technical discipline from a reputed institute.

Learn more about us at: https://timbleglance.com

Job Title: Technical AI Product Manager (Agentic AI)

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Key Responsibilities

1. Product Strategy & Roadmap: Own the end-to-end product lifecycle for AI-native and agentic products. Translate complex operational problems into AI-driven workflows and autonomous agent solutions.
2. Agentic AI Architecture: Prototyping multi-agent workflows using LangGraph, LangChain, and modern LLM tooling. Build systems featuring tool calling, structured memory, planning, and reflection capabilities.
3. Hands-on Development: Develop proof-of-concepts (PoCs) and MVPs using Python. Integrate LLM APIs, vector databases, retrieval systems, and custom prompt engineering techniques.
4.  Agile Execution: Convert stakeholder requirements into technical specifications, user stories, and high-quality PRDs. Lead sprint planning and agile ceremonies with backend and AI/ML teams.
5.  Performance & Metrics: Define and monitor AI-specific KPIs, including token latency, system reliability, contextual accuracy, and hallucination rates.

Required Skills & Qualifications

1. Experience: 4+ Years in Product Management or Technical Product Management (TPM).
2. Domain Expertise: Proven track record of shipping AI/ML, Generative AI, or LLM-based applications.
3. Technical Skills: Hands-on experience prototyping or designing AI agents/workflows. Strong programming literacy in Python to interface with data science frameworks.
4. Education: B.Tech/M.Tech in Computer Science or a related technical discipline from a reputed institute.

What We Offer

1.  Absolute ownership of the core agentic roadmap in a high-growth AI startup.
2. A collaborative, high-velocity workspace with zero corporate bureaucracy.
3. Competitive compensation packages and performance-driven trajectory.

Learn more about us at: https://timbleglance.com

Job Title: Technical Lead – Python/Django

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Key Responsibilities

·      Architecture & Design: Design, develop, and maintain robust, scalable, and secure backend microservices and RESTful APIs using Python and Django.

·      Technical Leadership: Lead code reviews, enforce engineering best practices (TDD, clean code, documentation), and optimize database queries and system performance.

·      Team Mentorship: Guide, mentor, and unblock a team of mid-to-senior software development engineers (SDEs), fostering a high-performance execution culture.

·      System Optimization: Optimize application performance, enhance caching mechanisms, manage task queues, and ensure system uptime and smooth deployment pipelines.

·      Cross-functional Collaboration: Work closely with Frontend, Product Management, DevOps, and AI/ML teams to align backend capabilities with the product roadmap.

Required Skills & Qualifications

·      Experience: 6+ years of core software engineering experience, with at least 2+ years in a technical leadership or mentoring role.

·      Core Expertise: Exceptional command over Python and deep, production-level expertise in the Django/Django framework.

·      Database Management: Strong proficiency with relational databases (PostgreSQL, MySQL) and optimization (indexing, complex query tuning).

·      Caching & Queues: Practical experience with caching layers (Redis, Memcached) and asynchronous task queues (Celery).

·      Architecture Patterns: Solid understanding of microservices architecture, system design principles, API security, and RESTful web services.

·      DevOps Awareness: Familiarity with Docker, CI/CD pipelines, and cloud infrastructure (AWS/GCP) is a major plus.

·      Education: B.Tech/M.Tech or MCA / MBA in a technical specialization from a reputed institute.

What We Offer

·      Opportunity to lead a core engineering vertical in a fast-growing AI startup.

·      A collaborative, high-energy work culture with zero bureaucratic friction.

·      Competitive compensation packages and performance-driven growth paths.

Learn more about us at: https://timbleglance.com

Position Overview

We are seeking an experienced ERPNext/Frappe Developer to join our dynamic team at Dhwani. The ideal candidate will have strong expertise in developing, customizing, and maintaining ERPNext applications built on the Frappe Framework. This role involves working on complex business solutions, custom module development, and ensuring seamless integration with various business processes.

Key Responsibilities

Development & Customization

1. Design, develop, and implement custom applications and modules on the Frappe Framework and ERPNext.
2. Customize existing ERPNext modules (Accounting, CRM, HR, Inventory, Manufacturing, etc.) to meet specific business requirements.
3. Build custom DocTypes, forms, reports, dashboards, and print formats.
4. Develop and maintain REST APIs for system integrations.
5. Write clean, efficient, and well-documented code in Python and JavaScript.

Technical Implementation

1. Understand client requirements for ERPNext and suggest optimal technical solutions
2. Handle all aspects of development including server-side, API, and client-side logic
3. Implement business logic using Frappe's document lifecycle hooks and controllers
4. Develop custom web portals, web pages, and web forms
5. Ensure smooth transitions for customizations during Frappe/ERPNext upgrades

System Management

1. Manage ERPNext installations, configurations, and deployments
2. Perform system updates, upgrades, and maintenance
3. Debug and troubleshoot technical issues, providing timely solutions
4. Work with MariaDB/MySQL databases and write complex queries
5. Implement and manage version control using Git

Collaboration & Documentation

1. Collaborate with business analysts and stakeholders to gather and refine requirements
2. Write functional and development specifications
3. Participate in code reviews and contribute to development best practices
4. Provide technical guidance and support to junior developers

Required Qualifications

Experience

1. Minimum 2-4 years of hands-on experience with Frappe Framework and ERPNext development and customizations
2. Proven track record of delivering live ERPNext projects that can be showcased
3. Experience in customizing ERPNext modules across different business domains
4. We are also open to hire Interns (With PPO Opportunity) who demonstrates strong DSA and coding fundamentals, good understanding of Python programming, knowledge and exposure of MySQL database, strong logical thinking, problem solving skills along with interest in working on frappe framework and enthusiasm to build challenging technology solutions for social impact. High-performing interns will receive a Pre-Placement Offer (PPO) based on performance. Internship will be of 3 months with monthly stipend in between 15k-20k based on interview performance.

Technical Skills

Core Technologies:  

1. Strong proficiency in Python programming
2. Solid experience with JavaScript, HTML, CSS
3. Working knowledge of Jinja templating.
4. Experience with jQuery and Bootstrap framework

Frappe/ERPNext Expertise:  

1. Deep understanding of Frappe Framework architecture.
2. Experience with DocType creation, customization, and management.
3. Knowledge of Frappe's ORM, REST API capabilities, and hooks system.
4. Understanding of ERPNext modules and business workflows

Database & Infrastructure:  

1. Proficient in MariaDB/MySQL database management.
2. Experience with Linux operating systems.
3. Knowledge of Git version control.
4. Understanding of web server configurations and deployment.

Professional Skills

1. Strong analytical and problem-solving abilities
2. Excellent communication and collaboration skills
3. Ability to work effectively in team environments
4. Self-starter with ability to take ownership of projects
5. Attention to detail and commitment to quality code

This is a work-from-office role in Gurgaon, Haryana

Job Title: Product Lead or Tech Lead (AI & Infrastructure)

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3. AI Solutions

Role Overview-You will be the architectural backbone of Timble’s AI engine. This role requires a strong backend & systems mindset with exposure to AI/ML systems—balancing the development of high-accuracy fraud detection models with the scalable infrastructure required to run them.

Key Responsibilities

·      Engineering Leadership: Lead the development of our core AI products, including Bank Statement Analyzers, Face Match technology, and Electronic Residence Physical Verification (ERPV).

·      AI/ML Architecture: Design and deploy AI/ML-driven systems for document intelligence, fraud detection, and automation to enhance real-time intelligence.

·      Delivery Ownership: Take end-to-end ownership of features and ensure timely delivery in high-stakes production environments.

·      System Design & Scalability: Design and optimize high-throughput, low-latency API systems capable of handling real-world production loads across our 30+ high-quality APIs.

·      Hands-on Contribution: Remain hands-on with code when required, especially for critical modules, core architecture decisions, and troubleshooting.

·      Practical AI Application: Work on integrating and scaling AI/ML components in production. You must have the ability to apply complex AI solutions to solve real-world business problems.

·      Technical Strategy & InfoSec: Oversee Information Security protocols to protect proprietary financial data. Lead IP-related technical work, including patent-pending research for our authentication engines.

·      Mentorship: Act as the technical North Star for SDE-1 and SDE-2 engineers, instilling a culture of clean code, scalability, and cloud economics.

What We’re Looking For

·      Technical Expertise: Strong backend engineering expertise (Python or similar), with experience in building and maintaining scalable systems. Exposure to ML frameworks (TensorFlow/PyTorch) is a plus.

·      Domain Knowledge: Previous experience in Fintech, Cybersecurity, or BFSI tech stacks is highly preferred.

·      Infrastructure Skills: Solid experience with cloud infrastructure (AWS/GCP/Azure) and maintaining high availability.

·      Vision: The ability to translate complex fraud patterns into automated, executable code and a passion for "efficiency by design."

Learn more about us at: https://timbleglance.com

What we're building

We're a small, sharp team — founders, IIT/IIM folks, and industry veterans who've done this before. No bureaucracy, no layers, no meaningless standups. You'll work directly with the founding team on problems that are genuinely hard.

What we need from you

You've spent 4–8 years in AI/ML, and at least 2 of those years building real multi-agent systems — not demos, not POCs that never shipped. You've worked on at least 2 multi-agent platforms (AutoGen, CrewAI, LangGraph, custom orchestration — whatever, as long as agents were actually coordinating and not just chained prompts).

You think about:

• Agent memory, state, and context management
• Inter-agent communication and task delegation
• Failure handling, retries, and graceful degradation
• Tool use, MCP, and external system integration
• Evaluation and observability of agent behaviour

You're probably a fit if:

• You've debugged an agent loop at 11pm and found it weirdly satisfying
• You have opinions about when not to use an agent
• You care about systems that work in production, not just on your laptop

You're not a fit if:

• Your portfolio is mostly RAG pipelines and chatbots
• Your multi-agent experience is only a tutorial project or a hackathon demo

What we offer

• Best-in-class pay — we benchmark against top-tier tech and don't lowball on talent
• Direct access to founders and a senior team of IIT/IIM grads and industry veterans
• Flexible work — async-friendly, output-driven, no performative office hours
• Real technical ownership — you'll make architecture decisions, not just implement them
• Small team means your work ships fast and actually matters

Why Sentiaflow, honestly We're early. That means some things aren't figured out yet. But it also means the person we hire here will have shaped how this company thinks about agentic systems from day one. If you want to inherit a codebase and execute tickets, we're not the right place. If you want to build something from scratch with people who take the craft seriously, let's talk.

How we hire A quick intro call to get to know each other. If there's a fit, show us something you've built — a demo, a walkthrough, a system you're proud of. That's the interview. No better signal than watching someone talk about their own work.

About the Role 

We are seeking an experienced Cyber Security Specialist who can operate across both offensive and defensive security disciplines. This dual-role professional will lead Vulnerability Assessment and Penetration Testing (VAPT) engagements, act as the in-house Red Team to simulate real-world adversaries, and own the implementation and continuous improvement of the Information Security Management System (ISMS) aligned with ISO/IEC 27001 and related standards. You will combine hands-on offensive security work with governance, audit readiness, and stakeholder engagement across engineering, IT, legal, and executive leadership. 

Key Responsibilities 

VAPT & Red Team Operations 

• Plan, scope, and execute end-to-end Vulnerability Assessment and Penetration Testing (VAPT) engagements across web applications, mobile apps, APIs, networks, cloud environments, wireless, and physical infrastructure. 
• Act as the organization's in-house Red Team, simulating advanced persistent threat (APT) actors through adversary emulation, social engineering, phishing campaigns, and physical intrusion testing where authorized. 
• Design and execute Red Team operations aligned with MITRE ATT&CK, TIBER-EU, and similar frameworks; develop custom Tactics, Techniques, and Procedures (TTPs). 
• Conduct manual and automated exploitation, post-exploitation, lateral movement, privilege escalation, and persistence testing in production-like environments. 
• Develop custom exploits, payloads, scripts, and tooling (Python, PowerShell, Bash, C/C++, Go) to bypass security controls during sanctioned engagements. 
• Perform source code reviews, threat modeling, and secure architecture reviews of new and existing systems. 
• Coordinate Purple Team exercises with the Blue Team / SOC to validate detection coverage and improve defensive playbooks. 
• Produce high-quality VAPT and Red Team reports with executive summaries, technical findings, proof-of-concept exploits, risk ratings (CVSS), and prioritized remediation guidance. 
• Re-test remediated findings and track closure with engineering and IT teams through to verification. 

ISO Compliance & Governance 

• Lead the implementation, maintenance, and continual improvement of the ISMS in line with ISO/IEC 27001:2022, including scope definition, Statement of Applicability (SoA), and risk treatment plans. 
• Own and maintain ISO policies, procedures, controls, and documentation across the organization, ensuring alignment with ISO 27001, ISO 27017, ISO 27018, and ISO 22301. 
• Plan and coordinate internal and external audits; serve as the primary liaison with certification bodies, auditors, and regulators. 
• Conduct risk assessments, business impact analyses (BIA), and threat modeling; maintain a central risk register and drive remediation. 
• Map VAPT and Red Team findings to ISO 27001 Annex A controls and feed results into the risk management lifecycle. 
• Support compliance with adjacent frameworks: SOC 2, NIST CSF, GDPR, HIPAA, PCI-DSS, and DPDP Act (India), as applicable. 
• Define and report security and compliance KPIs/KRIs to senior leadership; prepare materials for management reviews and board updates. 
• Develop and deliver security awareness training, phishing simulations, and role-based secure-coding training. 
• Drive third-party / vendor risk management, including security questionnaires, contractual clauses, and ongoing monitoring. 
• Partner with engineering and DevOps to embed security into the SDLC, CI/CD pipelines, and cloud architectures (DevSecOps). 

Incident Response & Continuous Improvement 

• Support incident response activities: detection, triage, containment, eradication, recovery, and post-incident reviews. 
• Maintain business continuity and disaster recovery plans; coordinate BCP/DR testing and tabletop exercises. 
• Stay current on emerging threats, CVEs, attacker techniques, regulatory changes, and ISO standard updates; recommend and drive improvements. 

Required Qualifications 

• 8+ years of progressive experience in cyber security, with at least 4 years in hands-on offensive security (VAPT, penetration testing, or Red Team) and 3+ years in ISO 27001 implementation and audits. 
• Proven track record of leading VAPT engagements across web, mobile, API, network, cloud (AWS / Azure / GCP), and wireless environments. 
• Hands-on experience executing Red Team operations and adversary emulation aligned with MITRE ATT&CK. 
• Deep proficiency with offensive security tooling: Burp Suite Pro, Metasploit, Cobalt Strike (or open-source equivalents like Sliver, Mythic, Havoc), Nmap, Nessus, Nuclei, BloodHound, Impacket, Responder, and OWASP ZAP. 
• Strong scripting and exploit development skills in Python, PowerShell, Bash, and at least one compiled language (C/C++, Go, or Rust). 
• Proven hands-on experience leading an organization through ISO 27001 certification and surveillance audits end-to-end. 
• Strong working knowledge of ISO/IEC 27001:2022 (including Annex A controls), ISO 27002, ISO 27017, ISO 27018, and ISO 22301. 
• Solid understanding of security domains: IAM, network security, endpoint security, cloud security, application security (OWASP Top 10, API Security Top 10), and Active Directory attack paths. 
• Experience with risk assessment methodologies (ISO 27005, NIST 800-30) and the ability to translate offensive findings into business risk. 
• Strong report-writing, policy-drafting, and executive communication skills. 
• Bachelor's degree in Computer Science, Information Security, Engineering, or a related field (or equivalent experience). 

Preferred Qualifications 

• Offensive security certifications: OSCP, OSEP, OSWE, OSED, CRTO, CRTP, CRTE, CRTL, GPEN, GXPN, GWAPT, or CEH Practical. 
• Governance certifications: ISO 27001 Lead Implementer and/or Lead Auditor, CISSP, CISM, CISA, or CRISC. 
• Cloud security certifications (CCSP, AWS Security Specialty, Azure Security Engineer, or GCP Professional Cloud Security Engineer). 
• Published CVEs, security research, bug bounty achievements, or contributions to open-source security tools. 
• Experience with Active Directory / Entra ID red teaming, Kerberos attacks, and modern EDR/XDR evasion techniques. 
• Experience with container, Kubernetes, and serverless security testing. 
• Experience implementing or auditing additional frameworks: SOC 2 Type II, NIST CSF, NIST 800-53, HITRUST, or PCI-DSS. 
• Experience with GRC platforms (Vanta, Drata, Sprinto, ServiceNow GRC, Archer, OneTrust). 
• Experience in regulated industries: financial services, healthcare, SaaS, or critical infrastructure. 
• Experience briefing executive leadership, customers, and external auditors on offensive findings and remediation strategy. 

An excellent Python developer should have a higher understanding of the Python languages. They should be capable to accomplish a number of tasks using Python.Coordinating with development teams to find out the needs of the application.

• Using the Python programming language to create scalable code.
• Application testing and bug fixing.
• Creating the back-end elements.
• Utilising server-side logic to incorporate user-facing components.
• Evaluating and ranking customer feature requests.
• Integrating storage methods for data.
• Design and implementation of high-performance, low-latency applications.
• Working in concert with front-end programmers.
• Upgrading the functionality of current databases.
• Creating digital technologies to track online activity.

Skills Required ::

• Python Development
• C# Development
• .NET Framework / .NET Core
• REST API Development
• JSON Handling
• API Integrations
• Databases
• Query Optimization
• Git Version Control
• Azure DevOps
• Debugging & Troubleshooting
• Cloud Application Development

Company Overview:

Euphoric Thought Technologies is a dynamic and innovative technology company specializing in providing cutting-edge automation solutions for businesses across various sectors. We empower organizations to streamline their processes, enhance efficiency, and achieve significant cost savings through intelligent automation strategies. Our expertise spans across diverse platforms, enabling us to deliver tailored solutions that meet the unique needs of our clients.

Role Overview:

As a Python Automation Developer at Euphoric Thought Technologies, you will be instrumental in designing, developing, and implementing robust automation frameworks and scripts to ensure the quality and reliability of our software solutions. You will collaborate closely with development, QA, and DevOps teams to identify automation opportunities, build efficient test suites, and contribute to continuous integration and continuous delivery (CI/CD) pipelines. Your work will directly impact the speed and quality of our software releases, enabling us to deliver exceptional value to our customers.

Key Responsibilities:

- Design and develop automation frameworks using Python to validate .Net and C# based applications.

- Create and maintain automated test scripts for REST APIs, focusing on JSON data validation.

- Integrate automated tests into CI/CD pipelines using Azure DevOps to ensure continuous testing.

- Collaborate with developers and QA engineers to identify and resolve defects, improving overall software quality.

- Analyze test results and generate comprehensive reports to communicate testing progress and identify areas for improvement.

- Contribute to the development of automation best practices and standards to enhance team efficiency.

- Maintain and enhance existing automation frameworks to adapt to evolving project requirements.

- Participate in code reviews to ensure code quality and adherence to coding standards.

Required Skillset:

- Demonstrated proficiency in Python programming for automation, including experience with relevant libraries and frameworks.

- Solid understanding of software testing principles and methodologies, with experience in developing and executing automated test cases.

- Experience with REST API testing and JSON data validation.

- Familiarity with .Net and C# development environments.

- Experience with Azure DevOps for CI/CD and test automation.

- Strong analytical and problem-solving skills, with the ability to troubleshoot and resolve complex technical issues.

- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

- Bachelor's degree in Computer Science or a related field.

Byteridge is seeking a Rapid Prototyping Engineer specializing in AI Infrastructure & Optimization to work with our most strategic customers on deploying, fine-tuning, and optimizing large language models at scale. You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in computer science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)

• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

Solution Engineer

Pre-Sales · GTM Team

Noida | 🕐 Full-Time | 🧭 2+ Years

THE MISSION

We aren’t automating scripts, we’re deprecating the era of manual-heavy testing entirely. TestMu AI is building the world’s first AI-native platform where Agentic Intelligence autonomously plans, authors, and self-heals the entire Quality Engineering lifecycle.

The name “TestMu” comes from our community conference. Our users and team aren’t an audience, they’re the heartbeat of what we build. We believe AI augments human potential. It doesn’t replace it.

You will be the architect translating complex AI-native capabilities into empathetic, high-impact solutions for global engineering teams.

THE PILLARS OF IMPACT

🚀 1. Solution Design & Discovery (50%)  

• Lead technical discovery to diagnose customer pain points and map them to autonomous QE workflows.
• Architect and deliver high-stakes product demonstrations that prove the ROI of Agentic Intelligence.
• Design bespoke technical roadmaps that integrate TestMu AI into complex enterprise SDLCs. 
• Build deep trust with prospects by demonstrating a "solution-first" rather than "feature-first" approach.

⚙️ 2. Technical Validation & Trial Success (30%)

• Own the end-to-end technical POC lifecycle, ensuring prospects achieve "aha" moments through successful trials. 
• Troubleshoot automation framework migrations and environment configurations (Web, Mobile, API) in real-time. 
• Act as the technical pivot point, ensuring every trial meets its defined success criteria for deal closure.

🧠 3. Market Intel & Product Influence (20%)

• Synthesize technical customer feedback into actionable insights for the Product and Engineering squads.
• Develop competitive playbooks that highlight TestMu AI’s edge over legacy automation frameworks.
• Enable the broader Sales team by creating "gold standard" demo environments and technical documentation

WHAT AI GIVES YOU

TestMu AI Platform How you’ll use it: To demonstrate and architect autonomous testing agents for global enterprises.

Tool: ChatGPT Enterprise How you’ll use it: To accelerate the creation of custom scripts, technical docs, and competitive battlecards.

Tool: Internal AI Co-pilots How you’ll use it: To query internal product documentation and technical specs for rapid customer responses.

Who we're looking for:

Signal 1 — Automation Depth: NON-NEGOTIABLE. You must prove hands-on mastery of Selenium, Appium, Playwright, or Cypress.

Signal 2 — Articulation Power: You must demonstrate the ability to explain complex AI logic to both developers and C-suite stakeholders with clarity.

Signal 3 — Solutionizing Mindset: You must prove a prospect-first, empathetic approach that prioritizes solving the user's specific problem over a generic pitch.

Signal 4 — Technical Sales DNA: Minimum 2 years in a customer-facing engineering role, specifically within the B2B SaaS ecosystem.

This isn’t just a job. It’s where your career takes flight. Apply now and start building what’s next.

We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.

KEY RESPONSIBILITIES

End-to-End ML Development

•     Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.

•     Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.

•     Validate model performance using appropriate statistical techniques and domain knowledge.

MLOps & Production Deployment

•     Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.

•     Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.

•     Ensure model reliability, observability, and performance in live production environments.

Language Models & LLM Applications

•     Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.

•     Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.

•     Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.

•     Support exploratory work around LLM integration and prompt engineering for internal tooling.

Domain-Driven Analytics

•     Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.

•     Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.

•     Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.

REQUIRED QUALIFICATIONS

Education

•     Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.

Experience

•     2–4 years of hands-on experience in a data science or machine learning role.

•     Demonstrable experience deploying ML models in production environments (not just prototyping).

Technical Skills

•     Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).

•     Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.

•     Hands-on experience with BERT-family models and Hugging Face Transformers library.

•     Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.

•     Solid understanding of SQL and working with large structured/unstructured datasets.

•     Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).

GOOD TO HAVE

•     Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).

•     Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.

•     Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.

•     Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).

•     Contributions to open-source ML projects or published research.

THIS ROLE IS NOT FOR YOU IF…

•     You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.

•     Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.

Job Title: Product Lead or Tech Lead (AI & Infrastructure)

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3. AI Solutions

Role Overview-You will be the architectural backbone of Timble’s AI engine. This role requires a strong backend & systems mindset with exposure to AI/ML systems—balancing the development of high-accuracy fraud detection models with the scalable infrastructure required to run them.

Key Responsibilities

·      Engineering Leadership: Lead the development of our core AI products, including Bank Statement Analyzers, Face Match technology, and Electronic Residence Physical Verification (ERPV).

·      AI/ML Architecture: Design and deploy AI/ML-driven systems for document intelligence, fraud detection, and automation to enhance real-time intelligence.

·      Delivery Ownership: Take end-to-end ownership of features and ensure timely delivery in high-stakes production environments.

·      System Design & Scalability: Design and optimize high-throughput, low-latency API systems capable of handling real-world production loads across our 30+ high-quality APIs.

·      Hands-on Contribution: Remain hands-on with code when required, especially for critical modules, core architecture decisions, and troubleshooting.

·      Practical AI Application: Work on integrating and scaling AI/ML components in production. You must have the ability to apply complex AI solutions to solve real-world business problems.

·      Technical Strategy & InfoSec: Oversee Information Security protocols to protect proprietary financial data. Lead IP-related technical work, including patent-pending research for our authentication engines.

·      Mentorship: Act as the technical North Star for SDE-1 and SDE-2 engineers, instilling a culture of clean code, scalability, and cloud economics.

What We’re Looking For

·      Technical Expertise: Strong backend engineering expertise (Python or similar), with experience in building and maintaining scalable systems. Exposure to ML frameworks (TensorFlow/PyTorch) is a plus.

·      Domain Knowledge: Previous experience in Fintech, Cybersecurity, or BFSI tech stacks is highly preferred.

·      Infrastructure Skills: Solid experience with cloud infrastructure (AWS/GCP/Azure) and maintaining high availability.

·      Vision: The ability to translate complex fraud patterns into automated, executable code and a passion for "efficiency by design."

Learn more about us at: https://timbleglance.com

You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

Backend Developer

📍 Noida | 🕐 Full-Time | 🧭 Experience: 2–3 Years

The Mission

We aren't building traditional backend systems — we're powering the infrastructure behind Agentic Intelligence. TestMu AI is building the world's first AI-native platform where backend systems don't just serve requests, they enable autonomous decision-making, execution, and scale.

The name "TestMu" comes from our community conference. Our users and team aren't an audience — they're the heartbeat of what we build. We believe AI augments human potential. It doesn't replace it.

You'll be building the core backend systems that power AI-driven workflows — ensuring high performance, scalability, and reliability at every layer.

The Pillars of Impact

🚀 1. Core Backend & System Architecture (50%)

• Build and scale high-performance backend services and APIs
• Design efficient database schemas, query optimization, and data flows
• Write clean, logical, production-grade code (Python, Golang, or similar)
• Own system performance — latency, throughput, and reliability

⚙️ 2. Backend for AI Systems (30%)

• Develop backend systems supporting AI agents and autonomous workflows
• Handle large-scale data processing, async tasks, and event-driven systems
• Integrate backend infrastructure seamlessly with AI/ML components

🧠 3. Scalability & Distributed Systems (20%)

• Contribute to microservices architecture and service decomposition
• Build fault-tolerant, highly available distributed systems
• Optimize systems for high concurrency and real-time execution

Your Engineering Stack

Tech/ToolsPython / GolangBuilding core backend services and logic-heavy systemsAWS / GCPDeploying and scaling distributed backend infrastructureKafka / RabbitMQHandling asynchronous processing and event-driven workflows

The Bar

SignalCore Backend Experience2–3 years of hands-on experience building APIs, backend systems, and scalable servicesProblem-Solving AbilityStrong fundamentals in data structures, algorithms, and logical thinkingSystem Design UnderstandingAbility to design scalable backend systems with clear architectural thinkingOwnership & ExecutionExperience owning backend features end-to-end in a fast-paced environment

The Interview Loop · Screening for the Top 1%

RoundsRound I · Recruiter ScreenEvaluation of backend experience, problem-solving approach, and project depthRound II · Hiring ManagerDeep dive into backend projects, APIs, databases, and system design thinkingRound III · Domain LeadLive coding + backend problem-solving + discussion on scalability and distributed systemsFinal · LeadershipCulture fit, ownership mindset, and ability to operate in a high-velocity startup environment

Your Growth Trajectory TestMu AI is a high-growth environment where we promote based on complexity solved, not years of tenure. As a Backend Developer, you have a massive runway to scale from an Individual Contributor (IC) into a core Engineering Leadership role, working alongside pioneers in agentic intelligence.

Perks of the Future

• Health & Wellness: 100% premium covered insurance for you + family (spouse, kids, parents) with annual check-ups.
• Fuel for Innovation: Fresh, daily gourmet lunch and dinner served at our Noida HQ.
• Seamless Transit: Safe, GPS-enabled cab facilities for eligible shifts (home-office-home).
• POD Culture: Dedicated quarterly budgets for team-building, offsites, and collaborative celebrations.

Senior Data Engineer (Databricks, BigQuery, Snowflake)

Experience: 8+ Years in Data Engineering

Location: Remote | Onsite (Noida, Gurgaon, Pune, Nagpur, Jaipur, Gandhinagar)

Budget: Open / Competitive

Job Summary:

We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data solutions that support advanced analytics and machine learning initiatives. You will lead the development of reliable, high-performance data systems and collaborate closely with data scientists to enable data-driven decision-making.

In this role, we expect a forward-thinking professional who utilizes AI-augmented development tools (such as Cursor, Windsurf, or GitHub Copilot) to increase engineering velocity and maintain high code standards in a modern enterprise environment.

Key Responsibilities:

• Scalable Pipelines: Design, develop, and optimize end-to-end data pipelines using SQL, Python, and PySpark.
• ETL/ELT Workflows: Build and maintain workflows to transform raw data into structured, analytics-ready datasets.
• ML Integration: Partner with data scientists to deploy and integrate machine learning models into production environments.
• Cloud Infrastructure: Manage and scale data infrastructure within AWS and Azure ecosystems.
• Data Warehousing: Utilize Databricks and Snowflake for big data processing and enterprise warehousing.
• Automation & IaC: Implement workflow orchestration using Apache Airflow and manage infrastructure as code via Terraform.
• Performance Tuning: Optimize data storage, retrieval, and system performance across data warehouse platforms.
• Governance & Compliance: Ensure data quality and security using tools like Unity Catalog or Hive Metastore.
• AI-Augmented Development: Integrate AI tools and LLM APIs into data pipelines and use AI IDEs to streamline debugging and documentation.

Technical Requirements:

• Experience: 8+ years of core Data Engineering experience in large-scale enterprise or consulting environments.
• Languages: Expert proficiency in SQL and Python for complex data processing.
• Big Data: Hands-on experience with PySpark and large-scale distributed computing.
• Architecture: Strong understanding of ETL frameworks, data pipeline architecture, and data warehousing best practices.
• Cloud Platforms: Deep working knowledge of AWS and Azure.
• Modern Tooling: Proven experience with Databricks, Snowflake, and Apache Airflow.
• Infrastructure: Experience with Terraform or similar IaC tools for scalable deployments.
• AI Competency: Proficiency in using AI IDEs (Cursor/Windsurf) and integrating AI/ML models into production data flows.

Preferred Qualifications:

• Exposure to data governance and cataloging tools (e.g., Unity Catalog).
• Knowledge of performance tuning for massive-scale big data systems.
• Familiarity with real-time data processing frameworks.
• Experience in digital transformation and sustainability-focused data projects.

About Us :

CLOUDSUFI, a Google Cloud Premier Partner, a Data Science and Product Engineering organization building Products and Solutions for Technology and Enterprise industries. We firmly believe in the power of data to transform businesses and make better decisions. We combine unmatched experience in business processes with cutting edge infrastructure and cloud services. We partner with our customers to monetize their data and make enterprise data dance.

Our Values :

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement :

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace.

Role : Lead AI/Senior Engineer-AI

Location : Noida, Delhi/NCR

Experience : 5- 12 years

Education : BTech / BE / MCA / MSc Computer Science

Must Haves :

Conversational AI & NLU :

- Advanced proficiency with Dialogflow CX

- Intent classification, entity extraction, conversation flow design

- Experience building structured dialogue flows with routing logic CCAI platform familiarity

Agentic AI & Multi-Step Reasoning :

- Production experience with Google ADK (or LangChain/LangGraph equivalent)

- Multi-step reasoning and tool orchestration capability

- Tool-use patterns and function calling implementation

RAG Systems & Knowledge Management :

- Hands-on Vertex AI RAG Engine experience (or equivalent)

- Semantic search, chunking strategies, retrieval optimization

- Document processing pipelines (PDF parsing, chunking)

LLM/GenAI & Prompt Engineering :

- Production experience with Gemini models

- Advanced prompt engineering for customer support

- Langfuse experience for prompt management

Google Cloud Platform & Vertex AI :

- Advanced Vertex AI proficiency (Generative AI APIs, Agent Engine)

- Cloud Functions and Cloud Run deployment experience

- BigQuery for conversation analytics

API Integration :

- Genesys Cloud CX integration experience

- REST API design and webhook implementation

- Enterprise authentication patterns (OAuth 2.0)

Good To Have :

Conversational AI & NLU :

- Multi-language support implementation (Spanish/English)

- Telephony integration (speech recognition, TTS, DTMF)

- Barge-in handling and voice optimization

Agentic AI :

- Agent state management and session persistence

- Advanced fallback strategies and error recovery

- Dynamic tool selection and evaluation

RAG Systems :

- Re-ranking and advanced retrieval quality metrics

- Query expansion and context-aware retrieval

- Corpus organization strategies

LLM/GenAI :

- Prompt versioning, A/B testing, iterative refinement

- Prompt injection mitigation strategies

- In-context learning, few-shot, chain-of-thought techniques

LLMOps & Observability :

- Vertex AI Evaluation Service experience

- Groundedness, relevance, coherence, safety metrics

- Trace-level debugging with Cloud Trace

- Centralized logging strategies

Google Cloud :

- Application Integration connectors

- VPC Service Controls and enterprise security

- Cloud Pub/Sub for event-driven systems

Enterprise Integration :

- Third-party AI agent orchestration (SAP Joule, ServiceNow AI, Agentforce)

- Salesforce, SAP, ServiceNow integration patterns

- Context passage strategies for escalations

Architecture & System Design :

- Configuration-driven systems (Meta-Agent patterns)

- Microservices and containerization

- Scalable, multi-tenant system design

- Disaster recovery and failover strategies

Product Quality & KPIs :

- Customer support metrics expertise (CSAT, SSR, escalation rate)

- A/B testing and experimentation frameworks

- User feedback loop implementation

Deliverables :

- Architecture Design : End-to-end platform architecture, data flow diagrams, Dialogflow CX vs. ADK routing decisions

- Conversational Flows : 15+ dialogue flows covering billing, networking, appointments, troubleshooting, and escalations

- ADK Agent Implementation : Complex reasoning agents for technical support, account analysis, and context preparation

- RAG Pipeline : Document processing, chunking configuration, corpus organization (product docs, support articles, policies, promotions)

- Prompt Management : System prompts, Langfuse setup, playbook governance, version control

- Quality Framework : Evaluation pipeline, metrics dashboards, automated assessment, continuous improvement recommendations

- Integration Layer : Genesys handoff, webhook integrations, Application Integration setup, session management

- Testing & Validation : Conversation flow tests, performance testing (latency, throughput, 1000 concurrent users), security validation

- Response time <2 seconds (p95), 99.9% uptime, 1000 concurrent conversations

- Data encryption (TLS 1.2+, AES-256 at rest), PII redaction, 1-year data retention

- Graceful degradation and fallback mechanisms

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

Key Responsibilities

·      Design, develop, and deploy machine learning models for real-world business problems

·      Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

·      Implement and manage MLOps pipelines for scalable and reproducible workflows

·      Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

·      Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

·      Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

·      Optimize model performance and ensure production stability

·      Stay updated with the latest advancements in AI/ML and GenAI ecosystems

Required Skills & Qualifications

·      4+ years of experience in Data Science / Machine Learning

·      Strong programming skills in Python

·      Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

·      Solid understanding of MLOps practices and tools

·      Experience with MLflow or similar model lifecycle tools 

·      Practical experience in Generative AI (GenAI), including working with LLMs

·      Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

·      Strong understanding of data structures, algorithms, and statistics

·      Experience with cloud platforms (AWS/GCP/Azure) is a plus

Good to Have

·      Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

·      Exposure to Docker, Kubernetes, and CI/CD pipelines

·      Knowledge of data engineering workflows 

Key Responsibilities:

• ☁️ Manage cloud infrastructure and automation on AWS, Google Cloud (GCP), and Azure.
• 🖥️ Deploy and maintain Windows Server environments, including Internet Information Services (IIS).
• 🐧 Administer Linux servers and ensure their security and performance.
• 🚀 Deploy .NET applications (ASP.Net, MVC, Web API, WCF, etc.) using Jenkins CI/CD pipelines.
• 🔗 Manage source code repositories using GitLab or GitHub.
• 📊 Monitor and troubleshoot cloud and on-premises server performance and availability.
• 🤝 Collaborate with development teams to support application deployments and maintenance.
• 🔒 Implement security best practices across cloud and server environments.

Required Skills:

• ☁️ Hands-on experience with AWS, Google Cloud (GCP), and Azure cloud services.
• 🖥️ Strong understanding of Windows Server administration and IIS.
• 🐧 Proficiency in Linux server management.
• 🚀 Experience in deploying .NET applications and working with Jenkins for CI/CD automation.
• 🔗 Knowledge of version control systems such as GitLab or GitHub.
• 🛠️ Good troubleshooting skills and ability to resolve system issues efficiently.
• 📝 Strong documentation and communication skills.

Preferred Skills:

• 🖥️ Experience with scripting languages (PowerShell, Bash, or Python) for automation.
• 📦 Knowledge of containerization technologies (Docker, Kubernetes) is a plus.
• 🔒 Understanding of networking concepts, firewalls, and security best practices.

What we are looking for:

We are looking for a motivated AI Developer with 1–3 years of experience to join our team and build cutting-edge applications powered by Large Language Models (LLMs). You will work on designing, developing, and optimizing intelligent systems using modern AI frameworks and tools.

Responsibilities:

• Design and develop applications leveraging Large Language Models (LLMs)
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines
• Work with frameworks like LangChain, LangGraph, or similar LLM orchestration tools
• Integrate and manage vector databases (e.g., Pinecone, Weaviate, Qdrant, FAISS)
• Implement prompt engineering strategies and improve model responses
• Develop scalable and efficient AI system architectures
• Monitor, debug, and optimize LLM applications using observability tools (e.g., Langfuse or similar)
• Collaborate with backend and product teams to integrate AI features into production systems
• Stay updated with the latest advancements in AI/LLM ecosystem

Skills:

• 1–3 years of hands-on experience in AI/ML or backend development with AI exposure
• Strong understanding of LLMs and generative AI concepts
• Experience with LangChain, LangGraph, or similar frameworks
• Practical experience with RAG architectures and pipelines
• Hands-on experience with vector databases (e.g., Pinecone, Qdrant, Weaviate, FAISS)
• Familiarity with observability tools like Langfuse, Helicone, or similar
• Proficiency in Python (preferred) or Node.js
• Experience working with APIs (OpenAI, Anthropic, etc.)
• Understanding of embeddings, chunking, and retrieval strategies
• Good problem-solving and debugging skills

Experience:

• 1-3 years of experience in AI application development

Remuneration: Industry Standard basis experience

Job Title: Devops Engineer

Location: Delhi, Arjan Garh

Job Type: Full-Time

IMMEDIATE JOINERS REQUIRED

About Us:

Timble is a forward-thinking organization dedicated to leveraging cutting-edge technology to solve real-world problems. Our mission is to drive innovation and create impactful solutions through artificial intelligence and machine learning.

About the Role

We are looking for a high-ownership Senior DevOps Engineer to architect and maintain the mission-critical infrastructure supporting our global algorithmic trading operations. You will be the bridge between development and live trading, ensuring zero-latency performance and 100% system availability.

Key Responsibilities

• Infrastructure Architecture: Design scalable, fault-tolerant systems for high-frequency trading environments.
• Performance Optimization: Tune Linux servers and Python environments for maximum speed and efficiency.
• Incident Management: Lead real-time response for live trading systems, performing RCA and preventive fixes.
• Automation & CI/CD: Build and enhance robust pipelines using Docker, Jenkins, and Ansible.
• Proactive Monitoring: Implement advanced logging and alerting (Prometheus/Grafana) to ensure high uptime.
• Database Admin: Manage relational databases and write optimized SQL for operational reporting.
• Mentorship: Guide junior DevOps members and maintain rigorous system documentation.

Technical Requirements

• OS/Scripting: Advanced Linux Admin and expert-level Python scripting.
• IaC & Tools: Hands-on experience with Ansible, Terraform, and Docker.
• CI/CD: Proficiency in Jenkins or GitLab CI.
• Data: Strong SQL skills with experience in performance tuning.
• Education: B.Tech/M.Tech in Computer Science or related engineering field.

We are looking to recruit an expert for backend software development at Webnyay. We are an enterprise SaaS startup catering to India and international markets. We are now growing fast and need a rockstar senior software developer who is an expert in Python/Django and GCP.

What we are looking for:

• At least 6 years of professional software development experience.
• At least 4 years of experience with Python & Django.
• Proficiency in Natural Language Processing (tokenization, stopword removal, lemmatization, embeddings, etc.)
• Experience in computer vision fundamentals, particularly object detection concepts and architectures (e.g., YOLO, Faster R-CNN)
• Experience in search and retrieval systems and related concepts like ranking models, vector search, or semantic search techniques
• Experience with multiple databases (relational and non-relational).
• Experience with hosting on GCP and other cloud services.
• Familiar with continuous integration and other automation.
• Focus on code quality and writing scalable code.
• Ability to learn and adopt new technologies depending on business requirements.
• Prior startup experience will be a plus!

Some of your responsibilities would include:

• Work closely in a highly AGILE environment with a team of engineers.
• Create and maintain technical documentation of technical design and solution.
• Build products/features that are highly scalable, secure, highly available, high performing and cost-effective.
• Help team in debugging.
• Perform code reviews.
• Understand the full feature set/ implementation and architecture of the applications.
• Analyze business goals and product requirements and contribute to application architecture design, development and delivery.
• Provide technical expertise for every phase of the project lifecycle; from concept development to solution design, implementation, optimization and support.
• Act as an Interface with business teams to understand and create technical specifications for workable solutions within the project.
• Explore and work with LLM APIs and Generative AI.
• Make performance-related recommendations, identify and eliminate performance bottlenecks (hardware, software, configuration); drive performance tuning, re-design and re-factoring.
• Participate in the software development lifecycle, which includes research, new development, modification, security, reuse, re-engineering and maintenance of common component libraries.
• Participate in product definition and feature prioritization.
• Collaborate with internal teams and stakeholders across business verticals.

Job Details

- Job Title: Android Developer

- Industry: IT- Services

- Function - Information technology (IT)

- Experience Required: 5-8 years

- Employment Type: Full Time

- Job Location: Delhi

- CTC Range: Best in Industry

Criteria:

· Strong technical background in Android application development and Kotlin

· Looking candidates having 5+ years of experience.

· Need candidates from Delhi NCR Only.

· All Academic backgrounds acceptable (except BCA).

· Immediate Joiners Preferred

· Candidate must have some experience working with IoT devices.

· Candidate should have experience working with Camera model X.

· Candidate's Academic scores must be 70% or above.

· Candidate having fluent communication will be an added advantage.

Job Description 

About the Role:

Senior Android Team Lead will be responsible for testing, QC, debugging support for various Android and Java software/servers for products developed or procured by the company. The role includes debugging integration issues, handling on-field deployment challenges, and suggesting improvements or structured solutions. The candidate will also be responsible for scaling the architecture. You will work closely with other team members including Web Developers, Software Developers, Application Engineers, and Product Managers to test and deploy existing products. You will act as a Team Lead to coordinate and organize team efforts toward successful completion or demo of applications. This includes implementing projects from conception to deployment.

Responsibilities:

● Working with the Android SDK, Java, Kotlin, NDK

● Handling different Android versions and screen sizes

● Applying Android UI design principles, patterns, and best practices

Requirements:

● Strong technical background in Android application development and Kotlin

● Solid programming skills

● Detail-oriented with strong attention to specifics

● Excellent written and verbal communication skills

● Strong analytical and quick problem-solving ability

● Ability to quickly document requirements from open discussions

● Fast typing skills for documentation and communication

● Familiarity with JIRA, EPICs, Excel, Google Sheets, and Agile methodologies

● Team player with leadership qualities

● Decision-making ability and team management skills

● Interest in working in a startup environment with cutting-edge products

● Experience with design and architecture patterns

● Understanding of testing processes, debugging, code versioning, and repositories

● UI/UX experience

● Strong knowledge of Java & Kotlin

● Software development experience with strong coding skills

● Experience building services for data delivery to mobile clients

● Experience with relational and non-relational databases

● Knowledge of REST and JSON data handling

● Experience with libraries like Retrofit, RxJava, Dagger 2, Lottie

● Server integration (REST endpoints)

● Experience with AWS stack and Linux

● Apps shipped and available on Google Play

● Backend API development

● Familiarity with Android Studio, Eclipse IDE

● Good knowledge of mobile hardware, software, and operating systems

● Willingness to work in a fast-paced startup environment

● Strong oral communication and presentation skills

● Team-oriented, with a positive approach to technology and engineering

● Result-oriented with a focus on efficiency and timeliness

● Strong self-awareness and ability to work under deadlines

● Proficiency in Microsoft Project, PowerPoint, Excel, Word

● Willingness to mentor and manage team members

● Willing to travel 5–10% of the time for demos, training, and collaboration

Preferred Background:

● Understanding of Artificial Intelligence and Machine Learning

● B.S. / M.S. in Computer Science, Electrical, or Electronics Engineering

● 5+ years’ experience with Android, Java Server, JSP

● Experience with Virtual Reality and Augmented Reality

● Familiarity with Test-Driven Development

● Background in CS or ECE

● Python experience is a big plus

● iOS development knowledge (not mandatory)

● Strong foundation in data structures and algorithms

JOB DETAILS:

* Job Title: Specialist I - DevOps Engineering

* Industry: Global Digital Transformation Solutions Provider

* Salary: Best in Industry

* Experience: 7-10 years

* Location: Bengaluru (Bangalore), Chennai, Hyderabad, Kochi (Cochin), Noida, Pune, Thiruvananthapuram

Job Description

Job Summary:

As a DevOps Engineer focused on Perforce to GitHub migration, you will be responsible for executing seamless and large-scale source control migrations. You must be proficient with GitHub Enterprise and Perforce, possess strong scripting skills (Python/Shell), and have a deep understanding of version control concepts.

The ideal candidate is a self-starter, a problem-solver, and thrives on challenges while ensuring smooth transitions with minimal disruption to development workflows.

Key Responsibilities:

• Analyze and prepare Perforce repositories — clean workspaces, merge streams, and remove unnecessary files.
• Handle large files efficiently using Git Large File Storage (LFS) for files exceeding GitHub’s 100MB size limit.
• Use git-p4 fusion (Python-based tool) to clone and migrate Perforce repositories incrementally, ensuring data integrity.
• Define migration scope — determine how much history to migrate and plan the repository structure.
• Manage branch renaming and repository organization for optimized post-migration workflows.
• Collaborate with development teams to determine migration points and finalize migration strategies.
• Troubleshoot issues related to file sizes, Python compatibility, network connectivity, or permissions during migration.

Required Qualifications:

• Strong knowledge of Git/GitHub and preferably Perforce (Helix Core) — understanding of differences, workflows, and integrations.
• Hands-on experience with P4-Fusion.
• Familiarity with cloud platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes).
• Proficiency in migration tools such as git-p4 fusion — installation, configuration, and troubleshooting.
• Ability to identify and manage large files using Git LFS to meet GitHub repository size limits.
• Strong scripting skills in Python and Shell for automating migration and restructuring tasks.
• Experience in planning and executing source control migrations — defining scope, branch mapping, history retention, and permission translation.
• Familiarity with CI/CD pipeline integration to validate workflows post-migration.
• Understanding of source code management (SCM) best practices, including version history and repository organization in GitHub.
• Excellent communication and collaboration skills for cross-team coordination and migration planning.
• Proven practical experience in repository migration, large file management, and history preservation during Perforce to GitHub transitions.

Skills: Github, Kubernetes, Perforce, Perforce (Helix Core), Devops Tools

Must-Haves

Git/GitHub (advanced), Perforce (Helix Core) (advanced), Python/Shell scripting (strong), P4-Fusion (hands-on experience), Git LFS (proficient)

Review Criteria:

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred:

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria:

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities:

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate:

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field. 

Company: Ethara AI

Location: Gurgaon (Work From Office)

Employment Type: Full-Time

Experience Required: 2–4 Years

Open Roles: Software Engineers (Python Fullstack)

About Us

Ethara AI is a leading AI and data services company in India, specializing in building high-quality, domain-specific datasets for Large Language Model (LLM) fine-tuning. Our work bridges the gap between academic learning and real world AI applications, and we are committed to nurturing the next generation of AI professionals.

Role Overview:-

We are looking for experienced Python Fullstack Software Engineers who can contribute to post training AI development workflows with strong proficiency in coding tasks and evaluation logic. This role involves working on high-impact AI infrastructure projects, including but not limited to:

 Code generation, validation, and transformation across Python, Java, JavaScript, and modern frameworks;

 Evaluation and improvement of model-generated code responses;

 Designing and verifying web application features, APIs, and test cases used in AI model alignment;

 Interpreting and executing task specifications to meet rigorous quality benchmarks;

 Collaborating with internal teams to meet daily throughput and quality targets within a structured environment.

Key Responsibilities:-

 Work on fullstack engineering tasks aligned with LLM post-training workflows;

 Analyze model-generated outputs for correctness, coherence, and adherence to task requirements;

 Write, review, and verify application logic and coding prompts across supported languages and frameworks;

 Maintain consistency, quality, and efficiency in code-focused deliverables;

 Engage with leads and PMs to meet productivity benchmarks (8–9 working hours daily);

 Stay updated with AI development standards and contribute to refining internal engineering processes.

Technical Skills Required:-

 Strong proficiency in Python and nice to have: Java, Node.js;

 Strong experience in frontend technologies: React.js, HTML/CSS, TypeScript;

 Familiarity with REST APIs, testing frameworks, and Git-based workflows;

 Ability to analyze, debug, and rewrite logic for correctness and clarity;

 Good understanding of model response evaluation and instruction-based coding logic

Qualifications:-

 Bachelor’s or Master’s degree in Computer Science, Engineering, or related field;

 2–4 years of experience in a software development role (Fullstack preferred);

 Prior exposure to AI/LLM environments or code-based evaluation tasks is a plus;

 Excellent written communication and logical reasoning abilities;

 Comfortable working from office in Gurgaon and committing to 8–9 hours of productive work daily

Why Join Us

 Be part of a high-growth team at the forefront of LLM post-training development;

 Work on real-world AI engineering problems with production-grade impact;

 Competitive compensation with performance-driven growth opportunities;

 Structured workflow, collaborative culture, and technically challenging projects

Review Criteria:

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred:

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria:

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities:

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate:

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field. 

Review Criteria

• Strong AI/ML Test Engineer
• 5+ years of overall experience in Testing/QA
• 2+ years of experience in testing AI/ML models and data-driven applications, across NLP, recommendation engines, fraud detection, and advanced analytics models
• Must have expertise in validating AI/ML models for accuracy, bias, explainability, and performance, ensuring decisions are fair, reliable, and transparent
• Must have strong experience to design AI/ML test strategies, including boundary testing, adversarial input simulation, and anomaly monitoring to detect manipulation attempts by marketplace users (buyers/sellers)
• Proficiency in AI/ML testing frameworks and tools (like PyTest, TensorFlow Model Analysis, MLflow, Python-based data validation libraries, Jupyter) with the ability to integrate into CI/CD pipelines
• Must understand marketplace misuse scenarios, such as manipulating recommendation algorithms, biasing fraud detection systems, or exploiting gaps in automated scoring
• Must have strong verbal and written communication skills, able to collaborate with data scientists, engineers, and business stakeholders to articulate testing outcomes and issues.
• Degree in Engineering, Computer Science, IT, Data Science, or a related discipline (B.E./B.Tech/M.Tech/MCA/MS or equivalent)
• Candidate must be based within Delhi NCR (100 km radius)

Preferred

• Certifications such as ISTQB AI Testing, TensorFlow, Cloud AI, or equivalent applied AI credentials are an added advantage.

Job Specific Criteria

• CV Attachment is mandatory
• Have you worked with large datasets for AI/ML testing?
• Have you automated AI/ML testing using PyTest, Jupyter notebooks, or CI/CD pipelines?
• Please provide details of 2 key AI/ML testing projects you have worked on, including your role, responsibilities, and tools/frameworks used.
• Are you willing to relocate to Delhi and why (if not from Delhi)?
• Are you available for a face-to-face round?

Role & Responsibilities

• 5 years’ experience in testing AIML models and data driven applications including natural language processing NLP recommendation engines fraud detection and advanced analytics models
• Proven expertise in validating AI models for accuracy bias explainability and performance to ensure decisions eg bid scoring supplier ranking fraud detection are fair reliable and transparent
• Handson experience in data validation and model testing ensuring training and inference pipelines align with business requirements and procurement rules
• Strong skills in data science equipped to design test strategies for AI systems including boundary testing adversarial input simulation and dri monitoring to detect manipulation aempts by marketplace users buyers sellers
• Proficient in data science for defining AIML testing frameworks and tools TensorFlow Model Analysis MLflow PyTest Python based data validation libraries Jupyter with ability to integrate into CICD pipelines
• Business awareness of marketplace misuse scenarios such as manipulating recommendation algorithms biasing fraud detection systems or exploiting gaps in automated scoring
• Education Certifications Bachelors masters in engineering CSIT Data Science or equivalent
• Preferred Certifications ISTQB AI Testing TensorFlowCloud AI certifications or equivalent applied AI credentials

Ideal Candidate

• 5 years’ experience in testing AIML models and data driven applications including natural language processing NLP recommendation engines fraud detection and advanced analytics models
• Proven expertise in validating AI models for accuracy bias explainability and performance to ensure decisions eg bid scoring supplier ranking fraud detection are fair reliable and transparent
• Handson experience in data validation and model testing ensuring training and inference pipelines align with business requirements and procurement rules
• Strong skills in data science equipped to design test strategies for AI systems including boundary testing adversarial input simulation and dri monitoring to detect manipulation aempts by marketplace users buyers sellers
• Proficient in data science for defining AIML testing frameworks and tools TensorFlow Model Analysis MLflow PyTest Python based data validation libraries Jupyter with ability to integrate into CICD pipelines
• Business awareness of marketplace misuse scenarios such as manipulating recommendation algorithms biasing fraud detection systems or exploiting gaps in automated scoring
• Education Certifications Bachelors masters in engineering CSIT Data Science or equivalent
• Preferred Certifications ISTQB AI Testing TensorFlow Cloud AI certifications or equivalent applied AI credentials

Job Summary

We are looking for a Marketing Data Engineering Specialist who can manage our real-estate

lead delivery pipelines, integrate APIs, automate data workflows, and support performance

marketing with accurate insights. The ideal candidate understands marketing funnels and has

strong skills in API integrations, data analysis, automation, and server deployments.

Key Responsibilities

 Manage inbound/outbound lead flows through APIs, webhooks, and sheet-based

integrations.

 Clean, validate, and automate datasets using Python, Excel, and ETL workflows.

 Analyse lead feedback (RNR, NT, QL, SV, Booking) and generate actionable insights.

 Build and maintain automated reporting dashboards.

 Deploy Python scripts/notebooks on Linux servers and monitor cron jobs/logs.

 Work closely with marketing, client servicing, and data teams to improve lead quality

and campaign performance.

Required Skills

 Python (Pandas, API requests), Advanced Excel, SQL

 REST APIs, JSON, authentication handling

 Linux server deployment (cron, logs)

 Data visualization tools (Excel, Google Looker Studio preferred)

 Strong understanding of performance marketing metrics and funnels

Qualifications

 Bachelor’s degree in Engineering/CS/Maths/Statistics/Marketing Analytics or related

field.

 Minimum 3 years of experience in marketing analytics, data engineering, or

marketing operations.

Preferred Traits

 Detail-oriented, analytical, strong problem-solver

 Ability to work in fast-paced environments

 Good communication and documentation skills

Review Criteria:

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred:

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria:

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities:

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate:

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field. 

We are seeking a motivated Data Analyst to support business operations by analyzing data, preparing reports, and delivering meaningful insights. The ideal candidate should be comfortable working with data, identifying patterns, and presenting findings in a clear and actionable way.

Key Responsibilities:

• Collect, clean, and organize data from internal and external sources
• Analyze large datasets to identify trends, patterns, and opportunities
• Prepare regular and ad-hoc reports for business stakeholders
• Create dashboards and visualizations using tools like Power BI or Tableau
• Work closely with cross-functional teams to understand data requirements
• Ensure data accuracy, consistency, and quality across reports
• Document data processes and analysis methods

About the role

Webnyay is looking for an experienced Backend Developer to build and scale reliable backend systems for our legal tech platform. You will work on core product architecture, high-performance APIs, and cloud-native services that support AI-driven workflows and large-scale data processing.

Responsibilities

• Develop backend services using Python, Django, and FastAPI
• Build scalable APIs and microservices for product features
• Implement event-driven and asynchronous workflows using Kafka
• Design and maintain backend integrations and data pipelines
• Deploy and manage services on Google Cloud Platform (GCP)
• Ensure performance, security, and reliability of backend systems
• Collaborate with product and engineering teams to deliver production-ready features

Requirements

• 4+ years of backend development experience
• Strong proficiency in Python
• Hands-on experience with Django and FastAPI
• Experience working with Kafka or similar messaging systems
• Working knowledge of GCP and cloud-based deployments
• Solid understanding of backend architecture and API design
• Experience with databases and production systems
• Experience building SaaS or platform-based products
• Exposure to AI-driven or data-intensive applications

Why Webnyay

• Build technology that improves access to justice
• Work on real-world, high-impact legal tech problems
• Collaborative and ownership-driven work culture
• Opportunity to grow with a fast-scaling startup

AI Agent Builder – Internal Functions and Data Platform Development Tools

About the Role:

We are seeking a forward-thinking AI Agent Builder to lead the design, development, and deployment, and usage reporting of Microsoft Copilot and other AI-powered agents across our data platform development tools and internal business functions. This role will be instrumental in driving automation, improving onboarding, and enhancing operational efficiency through intelligent, context-aware assistants.

This role is central to our GenAI transformation strategy. You will help shape the future of how our teams interact with data, reduce administrative burden, and unlock new efficiencies across the organization. Your work will directly contribute to our “Art of the Possible” initiative—demonstrating tangible business value through AI.

You Will:

•                 Copilot Agent Development: Use Microsoft Copilot Studio and Agent Builder to create, test, and deploy AI agents that automate workflows, answer queries, and support internal teams.

•                 Data Engineering Enablement: Build agents that assist with data connector scaffolding, pipeline generation, and onboarding support for engineers.

•                 Knowledge Base Integration: Curate and integrate documentation (e.g., ERDs, connector specs) into Copilot-accessible repositories (SharePoint, Confluence) to support contextual AI responses.

•                 Prompt Engineering: Design reusable prompt templates and conversational flows to streamline repeated tasks and improve agent usability.

•                 Tool Evaluation & Integration: Assess and integrate complementary AI tools (e.g., GitLab Duo, Databricks AI, Notebook LM) to extend Copilot capabilities.

•                 Cross-Functional Collaboration: Partner with product, delivery, PMO, and security teams to identify high-value use cases and scale successful agent implementations.

•                 Governance & Monitoring: Ensure agents align with Responsible AI principles, monitor performance, and iterate based on feedback and evolving business needs.

•                 Adoption and Usage Reporting: Use Microsoft Viva Insights and other tools to report on user adoption, usage and business value delivered.

What We're Looking For:

•                 Proven experience with Microsoft 365 Copilot, Copilot Studio, or similar AI platforms, ChatGPT, Claude, etc.

•                 Strong understanding of data engineering workflows, tools (e.g., Git, Databricks, Unity Catalog), and documentation practices.

•                 Familiarity with SharePoint, Confluence, and Microsoft Graph connectors.

•                 Experience in prompt engineering and conversational UX design.

•                 Ability to translate business needs into scalable AI solutions.

•                 Excellent communication and collaboration skills across technical and non-technical

Bonus Points:

•                 Experience with GitLab Duo, Notebook LM, or other AI developer tools.

•                 Background in enterprise data platforms, ETL pipelines, or internal business systems.

•                 Exposure to AI governance, security, and compliance frameworks.

•                 Prior work in a regulated industry (e.g., healthcare, finance) is a plus.

Required Skills: Advanced AWS Infrastructure Expertise, CI/CD Pipeline Automation, Monitoring, Observability & Incident Management, Security, Networking & Risk Management, Infrastructure as Code & Scripting

Criteria:

• 5+ years of DevOps/SRE experience in cloud-native, product-based companies (B2C scale preferred)
• Strong hands-on AWS expertise across core and advanced services (EC2, ECS/EKS, Lambda, S3, CloudFront, RDS, VPC, IAM, ELB/ALB, Route53)
• Proven experience designing high-availability, fault-tolerant cloud architectures for large-scale traffic
• Strong experience building & maintaining CI/CD pipelines (Jenkins mandatory; GitHub Actions/GitLab CI a plus)
• Prior experience running production-grade microservices deployments and automated rollout strategies (Blue/Green, Canary)
• Hands-on experience with monitoring & observability tools (Grafana, Prometheus, ELK, CloudWatch, New Relic, etc.)
• Solid hands-on experience with MongoDB in production, including performance tuning, indexing & replication
• Strong scripting skills (Bash, Shell, Python) for automation
• Hands-on experience with IaC (Terraform, CloudFormation, or Ansible)
• Deep understanding of networking fundamentals (VPC, subnets, routing, NAT, security groups)
• Strong experience in incident management, root cause analysis & production firefighting

Description

Role Overview

Company is seeking an experienced Senior DevOps Engineer to design, build, and optimize cloud infrastructure on AWS, automate CI/CD pipelines, implement monitoring and security frameworks, and proactively identify scalability challenges. This role requires someone who has hands-on experience running infrastructure at B2C product scale, ideally in media/OTT or high-traffic applications.

 Key Responsibilities

1. Cloud Infrastructure — AWS (Primary Focus)

• Architect, deploy, and manage scalable infrastructure using AWS services such as EC2, ECS/EKS, Lambda, S3, CloudFront, RDS, ELB/ALB, VPC, IAM, Route53, etc.
• Optimize cloud cost, resource utilization, and performance across environments.
• Design high-availability, fault-tolerant systems for streaming workloads.

2. CI/CD Automation

• Build and maintain CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI.
• Automate deployments for microservices, mobile apps, and backend APIs.
• Implement blue/green and canary deployments for seamless production rollouts.

3. Observability & Monitoring

• Implement logging, metrics, and alerting using tools like Grafana, Prometheus, ELK, CloudWatch, New Relic, etc.
• Perform proactive performance analysis to minimize downtime and bottlenecks.
• Set up dashboards for real-time visibility into system health and user traffic spikes.

4. Security, Compliance & Risk Highlighting

• Conduct frequent risk assessments and identify vulnerabilities in:

  o Cloud architecture

  o Access policies (IAM)

  o Secrets & key management

  o Data flows & network exposure

• Implement security best practices including VPC isolation, WAF rules, firewall policies, and SSL/TLS management.

5. Scalability & Reliability Engineering

• Analyze traffic patterns for OTT-specific load variations (weekends, new releases, peak hours).
• Identify scalability gaps and propose solutions across:
•   o Microservices
•   o Caching layers
•   o CDN distribution (CloudFront)
•   o Database workloads
• Perform capacity planning and load testing to ensure readiness for 10x traffic growth.

6. Database & Storage Support

• Administer and optimize MongoDB for high-read/low-latency use cases.
• Design backup, recovery, and data replication strategies.
• Work closely with backend teams to tune query performance and indexing.

7. Automation & Infrastructure as Code

• Implement IaC using Terraform, CloudFormation, or Ansible.
• Automate repetitive infrastructure tasks to ensure consistency across environments.

Required Skills & Experience

Technical Must-Haves

• 5+ years of DevOps/SRE experience in cloud-native, product-based companies.
• Strong hands-on experience with AWS (core and advanced services).
• Expertise in Jenkins CI/CD pipelines.
• Solid background working with MongoDB in production environments.
• Good understanding of networking: VPCs, subnets, security groups, NAT, routing.
• Strong scripting experience (Bash, Python, Shell).
• Experience handling risk identification, root cause analysis, and incident management.

Nice to Have

• Experience with OTT, video streaming, media, or any content-heavy product environments.
• Familiarity with containers (Docker), orchestration (Kubernetes/EKS), and service mesh.
• Understanding of CDN, caching, and streaming pipelines.

Personality & Mindset

• Strong sense of ownership and urgency—DevOps is mission critical at OTT scale.
• Proactive problem solver with ability to think about long-term scalability.
• Comfortable working with cross-functional engineering teams.

Why Join company?

• Build and operate infrastructure powering millions of monthly users.

• Opportunity to shape DevOps culture and cloud architecture from the ground up.

• High-impact role in a fast-scaling Indian OTT product.

Job Description: Python-Azure AI Developer

Experience: 5+ years

Locations: Bangalore | Pune | Chennai | Jaipur | Hyderabad | Gurgaon | Bhopal

Mandatory Skills:

• Python: Expert-level proficiency with FastAPI/Flask
• Azure Services: Hands-on experience integrating Azure cloud services
• Databases: PostgreSQL, Redis
• AI Expertise: Exposure to Agentic AI technologies, frameworks, or SDKs with strong conceptual understanding

Good to Have:

• Workflow automation tools (n8n or similar)
• Experience with LangChain, AutoGen, or other AI agent frameworks
• Azure OpenAI Service knowledge

Key Responsibilities:

• Develop AI-powered applications using Python and Azure
• Build RESTful APIs with FastAPI/Flask
• Integrate Azure services for AI/ML workloads
• Implement agentic AI solutions
• Database optimization and management
• Workflow automation implementation

Review Criteria:

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred:

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria:

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities:

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate:

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field. 

About VisibilityStack

VisibilityStack helps businesses connect with people who are actively searching for the solutions they offer, both on Google Search and in the new wave of AI-powered search tools.

Our AI agents identify what your audience is looking for, create content that answers those questions, and structure it so Google and AI systems can easily understand and recommend it. We also strengthen your online credibility through strategic backlinks and a strong social presence.

Everything is guided by real-time data. We focus on what works, remove what does not, and keep your content working around the clock. The result is simple: the right people can find you, trust you, and reach out when they need what you offer.

The Role

We need a Senior Engineer who ships production code that scales. You'll be the technical anchor—building critical infrastructure, solving complex problems, and mentoring junior developers through code reviews and pair programming.

You'll shape our future in four key ways: writing the code that becomes our foundation, being a key voice in engineering hiring decisions, helping establish the processes and patterns everyone follows, and having significant input on product decisions—your technical perspective directly influences what we build, not just how we build it. This isn't about managing people or writing performance reviews—it's about technical leadership through excellence.

What's in it for you:

1. Own mission-critical systems end-to-end — Your code directly generates customer revenue
2. Skip the politics, ship products — No layers of approval, no enterprise bureaucracy
3. Shape product direction — Your technical insights influence product strategy, not just implementation
4. Learn cutting-edge AI in production — Work with LLMs, vector databases, and agent orchestration at scale
5. Shape technical decisions and processes — Your input matters on how we build, not just what
6. Accelerated growth path — As we scale, you choose: become our technical lead or remain a deeply influential IC
7. Direct founder access — Collaborate on product vision, not just execute specs

Location: Janakpuri, Delhi (Hybrid - Maker's Schedule)

Our Work Philosophy:

We follow the Maker's Schedule, not the Manager's Schedule. This means uninterrupted blocks of deep work when you're building, and high-bandwidth collaboration when we're solving problems together.

In Practice:

1. In-office days: Whiteboard architecture sessions, rapid product iterations, deep dives into product strategy, complex debugging that needs three minds on one problem
2. Deep work days: Uninterrupted coding from wherever you work best—home, office, or that coffee shop with perfect noise levels
3. Balance by design: We optimize for both intense collaboration and deep focus

The best technical breakthroughs happen in two modes: intense in-person collaboration where ideas bounce rapidly, and deep solo work where complex problems get solved. We protect both.

Responsibilities

Technical Excellence

1. Build production systems that handle millions of AI operations daily
2. Write complex integrations that others can't figure out
3. Solve scaling problems before they become emergencies
4. Implement robust error handling and monitoring
5. Own critical infrastructure components end-to-end

Architecture & Code Quality

1. Design APIs that won't need v2 in 6 months
2. Make pragmatic technical decisions (boring tech when appropriate)
3. Help establish engineering processes—from code review to deployment
4. Create patterns and standards other engineers can follow
5. Lead code reviews that teach, not just critique
6. Balance shipping speed with technical sustainability

Hiring & Technical Assessment

1. Conduct technical interviews for engineering roles
2. Design practical coding assessments that test real skills
3. Provide strong input on hire/no-hire decisions
4. Partner with founders on technical requirements for roles
5. Help close strong candidates by selling the technical vision

Mentorship & Collaboration

1. Pair with junior developers on complex problems
2. Share knowledge through code reviews and documentation
3. Unblock teammates when they're stuck
4. Work directly with founders on technical strategy
5. Partner with product team on feature design and technical feasibility
6. Turn product ideas into technical specifications
7. Work directly with founders on technical strategy
8. Turn product ideas into technical specifications

Requirements

Must Have

1. 5-7 years of software engineering experience
2. Expert-level Python development skills
3. Production experience with LLMs (OpenAI, Anthropic, not just prototypes)
4. Built systems that scaled (and dealt with the failures)
5. Strong debugging skills—you fix what others can't
6. API design that makes sense to other developers
7. Git workflows and collaborative development

Strong Advantages

1. Previous early-stage startup experience
2. Production experience with vector databases (Pinecone, Weaviate, pgvector)
3. Elasticsearch or search infrastructure expertise
4. Built revenue-generating AI/ML systems
5. Experience with high-volume data pipelines
6. Contributed to open source projects
7. Informal mentorship or tech lead experience

Tech Stack

1. Backend: Python, FastAPI, PostgreSQL
2. AI/ML: OpenAI APIs, LangChain, Vector DBs
3. Infrastructure: AWS, Docker, GitHub Actions
4. Search: Elasticsearch (evaluating alternatives)

What We Offer

1. Early employee equity and financial upside
2. No bureaucracy—your code ships to production
3. Work on genuinely hard technical problems
4. Learn from and contribute to cutting-edge AI systems
5. Clear growth path as the team scales

REVIEW CRITERIA:

MANDATORY:

• Strong Senior/Lead DevOps Engineer Profile
• Must have 8+ years of hands-on experience in DevOps engineering, with a strong focus on AWS cloud infrastructure and services (EC2, VPC, EKS, RDS, Lambda, CloudFront, etc.).
• Must have strong system administration expertise (installation, tuning, troubleshooting, security hardening)
• Must have solid experience in CI/CD pipeline setup and automation using tools such as Jenkins, GitHub Actions, or similar
• Must have hands-on experience with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
• Must have strong database expertise across MongoDB and Snowflake (administration, performance optimization, integrations)
• Must have experience with monitoring and observability tools such as Prometheus, Grafana, ELK, CloudWatch, or Datadog
• Must have good exposure to containerization and orchestration using Docker and Kubernetes (EKS)
• Must be currently working in an AWS-based environment (AWS experience must be in the current organization)
• Its an IC role

PREFERRED:

• Must be proficient in scripting languages (Bash, Python) for automation and operational tasks.
• Must have strong understanding of security best practices, IAM, WAF, and GuardDuty configurations.
• Exposure to DevSecOps and end-to-end automation of deployments, provisioning, and monitoring.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• Candidates from NCR region only (No outstation candidates).

ROLES AND RESPONSIBILITIES:

We are seeking a highly skilled Senior DevOps Engineer with 8+ years of hands-on experience in designing, automating, and optimizing cloud-native solutions on AWS. AWS and Linux expertise are mandatory. The ideal candidate will have strong experience across databases, automation, CI/CD, containers, and observability, with the ability to build and scale secure, reliable cloud environments.

KEY RESPONSIBILITIES:

Cloud & Infrastructure as Code (IaC)-

• Architect and manage AWS environments ensuring scalability, security, and high availability.
• Implement infrastructure automation using Terraform, CloudFormation, and Ansible.
• Configure VPC Peering, Transit Gateway, and PrivateLink/Connect for advanced networking.

CI/CD & Automation:

• Build and maintain CI/CD pipelines (Jenkins, GitHub, SonarQube, automated testing).
• Automate deployments, provisioning, and monitoring across environments.

Containers & Orchestration:

• Deploy and operate workloads on Docker and Kubernetes (EKS).
• Implement IAM Roles for Service Accounts (IRSA) for secure pod-level access.
• Optimize performance of containerized and microservices applications.

Monitoring & Reliability:

• Implement observability with Prometheus, Grafana, ELK, CloudWatch, M/Monit, and Datadog.
• Establish logging, alerting, and proactive monitoring for high availability.

Security & Compliance:

• Apply AWS security best practices including IAM, IRSA, SSO, and role-based access control.
• Manage WAF, Guard Duty, Inspector, and other AWS-native security tools.
• Configure VPNs, firewalls, and secure access policies and AWS organizations.

Databases & Analytics:

• Must have expertise in MongoDB, Snowflake, Aerospike, RDS, PostgreSQL, MySQL/MariaDB, and other RDBMS.
• Manage data reliability, performance tuning, and cloud-native integrations.
• Experience with Apache Airflow and Spark.

IDEAL CANDIDATE:

• 8+ years in DevOps engineering, with strong AWS Cloud expertise (EC2, VPC, TG, RDS, S3, IAM, EKS, EMR, SCP, MWAA, Lambda, CloudFront, SNS, SES etc.).
• Linux expertise is mandatory (system administration, tuning, troubleshooting, CIS hardening etc).
• Strong knowledge of databases: MongoDB, Snowflake, Aerospike, RDS, PostgreSQL, MySQL/MariaDB, and other RDBMS.
• Hands-on with Docker, Kubernetes (EKS), Terraform, CloudFormation, Ansible.
• Proven ability with CI/CD pipeline automation and DevSecOps practices.
• Practical experience with VPC Peering, Transit Gateway, WAF, Guard Duty, Inspector and advanced AWS networking and security tools.
• Expertise in observability tools: Prometheus, Grafana, ELK, CloudWatch, M/Monit, and Datadog.
• Strong scripting skills (Shell/bash, Python, or similar) for automation.
• Bachelor / Master’s degree
• Effective communication skills

PERKS, BENEFITS AND WORK CULTURE:

• Competitive Salary Package
• Generous Leave Policy
• Flexible Working Hours
• Performance-Based Bonuses
• Health Care Benefits