50+ Python Jobs in India

 Job Description:

• Job title : Senior DevOps Engineer (On-Premises Automation)        
• Experience: 8+ years
• Location: Chennai / Pune / Hyderabad / Bangalore
• Shift: UK Shift
• Work Mode: Onsite (WFO)

Roles and Responsibilities:

• This engagement automates end-to-end infrastructure build provisioning across on-prem and Azure. The team will build a shared ServiceNow-led intake, approval, orchestration, and closed-loop status model, using Jenkins/Ansible for on-prem builds and Azure DevOps/Terraform for cloud builds. Automation includes standards, security/compliance controls, scan gates, CMDB/change updates, and handover.              

Key Responsibilities:

• Lead secure and repeatable on-prem build provisioning pipelines
• Lead Jenkins CI/CD for automated on-prem provisioning and configuration.
• Create pipeline templates for VM/physical host, OS deployment, configuration, certification, and rollback.
• Embed hardened-image validation, scan gates, secrets handling, approvals, and audit evidence.
• Lead Ansible roles, PowerShell modules, test automation, and code reviews.
• Implement logging, monitoring, and root-cause analysis; support UAT and hypercare.       

Required Qualifications:

• 8–10 years in DevOps, platform engineering, or infrastructure automation.
• Bachelor’s degree or equivalent experience.
• Jenkins
• Git, CI/CD
• Ansible, PowerShell
• Python, IaC
• security scanning, secrets management
• Windows/Linux.

AI Engineer

LLMs, Agents & AI Services

📍 Mumbai (On-site) | Full-time | 2-4 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

AI is core to how we design, deliver, and scale software for our customers.

We are hiring an AI Engineer for a dedicated client engagement building a complex production AI platform, working on the AI capabilities and agentic features at the core of the product.

The mandatory requirement for this role is at least one AI feature personally shipped to production for real users, with operational ownership.

The role suits someone who thinks quickly on solutioning, can take an ambiguous problem to a working prototype in days, and has the discipline to carry it through to production with predictable economics.

You will work alongside the Senior AI Engineer and the wider pod, with ownership of parts of the AI surface area of the product.

Responsibilities:

Solutioning and POCs

Translate ambiguous customer problems into working POCs at speed.

Pick the right model, framework, and architecture, and demonstrate value early before scaling investment.

LLM Application Development

Build AI features and services using LLM APIs from OpenAI, Anthropic, Google, and self-hosted open-weight models (Llama, Qwen, Mistral).

Choose the right model per use case based on cost, latency, capability, and context-window trade-offs.

Agentic System Design

Design and implement agentic workflows using LangGraph, CrewAI, AutoGen, LlamaIndex Agents, or custom orchestration.

Cover tool use, planning, memory, and multi-step reasoning appropriate to the problem.

API and Service Development

Build production AI services and APIs using Python and FastAPI.

Handle streaming responses, async processing, structured outputs, retries, and graceful degradation when models or tools fail.

Retrieval and Tool Integration

Implement RAG pipelines with vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma), embeddings, chunking strategies, hybrid search, and reranking.

Integrate external tools, internal APIs, and document sources through tool-calling and MCP-style patterns.

Cost Analysis and Unit Economics

Model the per-request and per-user cost of every AI feature before it ships.

Track token usage, prompt caching, batching, and model-routing strategies.

Drive measurable improvements in unit economics.

Production Hardening

Add observability and tracing (LangSmith, Langfuse, OpenTelemetry), guardrails, content safety checks, prompt injection defences, and fallback behaviour.

Prompt Engineering and Evaluation

Design, test, and iterate prompts with measured outcomes.

Build evaluation harnesses for accuracy, hallucination, latency, and cost.

Run benchmarks across models and prompt variants before locking in a design.

Requirements:

AI Feature Shipped to Production (Mandatory)

Must have personally built and shipped at least one AI feature that runs in production for real users, with operational ownership.

POCs, internal demos, and one-off scripts do not qualify.

2 to 4 Years of Professional Software or AI Engineering Experience

With at least one production AI feature owned end to end.

Strong Python Proficiency and API Development with FastAPI

Comfort with type hints, async, packaging, testing, streaming responses, and authentication.

Production-grade Python, not notebook-only code.

Hands-on Depth Across the LLM and Agent Stack

Working experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or self-hosted open-weight models (vLLM, Ollama, Together, Replicate).

Working familiarity with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Working knowledge of RAG, embeddings, and vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma).

Solutioning Speed and POC Velocity

Demonstrated ability to move from a fuzzy problem to a working prototype in days.

Strong instinct for what to build first, what to defer, and what to throw away.

Cost Discipline for Production AI

Ability to calculate, monitor, and optimise the cost of LLM APIs, tokens, embeddings, vector store usage, and infrastructure.

Treats unit economics as a first-class concern.

AWS Familiarity

Working knowledge of EC2, S3, IAM, and at least one of Bedrock, SageMaker, or equivalent.

Comfortable in a Fast-Moving Environment

Self-directed, comfortable with ambiguity, takes ownership without being asked, and ships under shifting priorities.

Strong Written and Spoken English Communication

Able to explain trade-offs to non-AI engineers, designers, product managers, and clients in plain language.

Nice to Have

• fine-tuning or LoRA, QLoRA, PEFT exposure
• MCP server authoring
• eval framework experience (LangSmith, Promptfoo, Ragas, DeepEval)
• open-source AI contributions
• multi-modal models (vision, audio)

Job Summary

We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.

Technical Skills

• Strong hands-on experience in Python and PySpark development.
• Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
• Experience with Power BI Data Modeling and Semantic Layer development.
• Proficiency in DAX (Data Analysis Expressions).
• Experience designing and managing Semantic Models in Power BI.
• Strong SQL skills and experience working with large datasets.
• Knowledge of data warehousing concepts and best practices.

Preferred Skills

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Exposure to modern data platforms like Databricks.
• Understanding of data governance and data quality frameworks.

About the Company

The client is revolutionising the way businesses operate through cutting-edge technological solutions. Their focus is on developing intelligent agents and agentic workflows that automate processes and eliminate the need for human effort wherever possible. By leveraging

advanced AI and machine learning, they create systems that enhance productivity and drive efficiency.

Their expertise extends to the fintech, healthcare and medical technology sectors, where they develop innovative solutions that improve patient outcomes and streamline medical operations.

From medical devices to healthcare platforms, their work sits at the intersection of technology and medicine, pushing the boundaries of what's possible. The team is dedicated to continuous learning and growth, ensuring the team members are always at the forefront of the tech landscape.

About the Role

This is a senior, hands-on engineering role at the heart of our product team. You will be one of the most technical people in the room — setting the architecture for our real-time voice AI

agents and building the hardest parts of it yourself. From the systems that power live conversations to the interfaces our clients rely on, you will own how the product is engineered end to end.

We are looking for a genuine lead full-stack engineer with the depth to make architecture decisions that hold up as we scale, and the appetite to still be in the code every day. You should be as comfortable designing the backend services behind a live voice agent as you are shaping a clean interface on top of them — and comfortable being the person others turn to when something is hard.

You will work directly with the founder and product leadership on a fast-moving product, with real influence over technical direction. This is a role for someone who wants ownership at the level of "how the whole thing is built," not just individual features — and who raises the bar for

everyone around them.

What You'll Own

Set the technical direction

• Own the architecture of our core systems — the real-time voice agents, backend
• services, data and APIs — making the decisions that keep the product fast, reliable and scalable as it grows.
• Lead the hardest engineering problems and solve them personally.
• Establish engineering standards — code quality, review practices, testing and technical patterns that the team builds to.
• Drive technical strategy with the founder and product leadership — shaping the roadmap, flagging risk early, and turning product ambition into a sound technical plan.

Build the product end to end

• Design, build and ship features across the stack — backend services, APIs and front-ends — owning them from idea to production.
• Build the client-facing surfaces — dashboards, review tools and configuration interfaces that let our clients run and trust the product.
• Design and evolve the data models and APIs that hold up as we scale across clients.

Make it reliable and fast

• Own production quality — put the monitoring and alerting in place so issues are caught before clients feel them, and performance stays within target.
• Care about performance — find and fix bottlenecks across the stack.
• Build for correctness — put the testing and evaluation in place that keeps the product behaving predictably as it changes.

Lead through the team

• Mentor and grow engineers — through code review, pairing, and setting a technical example others learn from.
• Multiply the team's output — unblock others and lift the overall quality of the codebase.
• Take features from ambiguity to done — turn a rough product goal into a shipped, working capability with minimal hand-holding, and help others do the same.

What We're Looking For

• 8+ years of professional software engineering experience, with significant depth across both backend and frontend and a track record of owning systems, not just features.
• Strong backend engineering, ideally in Python — building and scaling production services and APIs.
• Strong frontend engineering with a modern framework such as React — able to architect and build polished, responsive interfaces independently.
• Proven architecture and system-design ability — you have designed systems that scaled, and can reason clearly about trade-offs.
• Solid fundamentals across APIs, databases and cloud infrastructure.
• Experience building real-time and/or AI-powered products — or clear, demonstrable ability to lead in this area.
• A history of technical leadership — setting standards, mentoring engineers, and being trusted with the hardest problems — while remaining hands-on.
• Excellent communication and a genuine ownership mindset — someone who can be handed an ambiguous, high-stakes problem and be trusted to see it through.

Nice to Have

• Experience working with AI / large language models in production.
• Experience with voice or other real-time products.
• Exposure to healthcare, fintech, or other regulated / high-stakes domains.
• Experience as an early or senior engineer in a startup, where you set direction and wore many hats.

Company Description

Appiness Interactive Pvt. Ltd. is a Bangalore-based product development and UX firm that

specializes in digital services for startups to fortune-500s. We work closely with our clients to

create a comprehensive soul for their brand in the online world, engaged through multiple

platforms of digital media. Our team is young, passionate, and aggressive, not afraid to think

out of the box or tread the un-trodden path in order to deliver the best results for our clients.

We pride ourselves on Practical Creativity where the idea is only as good as the returns it

fetches for our clients.

About the Role

You will own the reliability of the distributed data systems, the streaming runtime and

processing engines that move hundreds of billions of rows per day for top-tier enterprises. This

is an SRE role for our big data stack: Kafka, Spark, Flink, Ray, Redis, and data warehouses, all

running on Kubernetes.

This is not a cloud-provisioning role. We are looking for someone who has lived inside stateful,

high-throughput systems in production who has chased down a broker outage, a checkpoint

stall, a crashlooping cache, and a sink that silently stopped writing, and who fixes the

architecture rather than the symptom. If keeping a large, busy data platform alive and fast is the

kind of problem you find satisfying, you will have a lot of fun working with us. This is a unique

opportunity to shape the foundation of a product that is defining the next wave of intelligent,

context-aware data movement.

Responsibilities

● Streaming & Data Plane Reliability: Own the health of our Kafka-based runtime

(managed via Strimzi on Kubernetes) - broker health, topic lifecycle and count

management, partition and throughput tuning, certificate/secret rotation, and version

upgrades - at a scale of hundreds of thousands of topics and hundreds of billions of rows

per day.

● Distributed Processing Engines: Operate and tune distributed system workloads in

production in collaboration with backend teams, resource allocation, autoscaling,

checkpointing, backpressure, and failure recovery for both batch and streaming jobs.

● Stateful Services: Run Redis clusters and other stateful systems reliably - failover,

persistence, liveness/readiness tuning, and capacity planning under heavy and bursty

load.

● Kubernetes & Operators: Take end-to-end ownership of Amazon EKS, Google GKE and

the operators (Strimzi and others) running our stateful data workloads - cluster lifecycle,

scaling, version upgrades, and resource governance.

● Observability: Build deep, data-aware monitoring - consumer lag, throughput, partition

skew, job latency, error rates - not just host and CPU metrics. Make the data plane's

behavior legible before it breaks.

● Incident Management: Lead root-cause analysis for distributed-systems failures (broker

outages, crashloops, sink decommissions, control-plane race conditions) and drive

durable fixes. Mitigate fast, but design out the recurrence.

● Infrastructure as Code & Automation: Provision and manage cloud infrastructure with

Terraform; build operational runbooks and automation, including for air-gapped/private

enterprise installs (pre-staged images, operator-facing procedures).

● Collaboration: Partner with platform, runtime, and connector engineering - and with

SREs and support - to ship and scale new data-movement features reliably in a

large-scale Linux environment.

Qualifications

● Experience: 6+ years in infrastructure, SRE, or DevOps, with significant time spent

operating production distributed data systems (not just application/cloud infra).

● Kafka: Deep, hands-on operational experience running Kafka at scale in production -

ideally on Kubernetes via Strimzi - including upgrades, topic/partition management,

performance tuning, and TLS/secret rotation.

● Distributed Processing (Strong Plus): Production experience operating one or more of

Spark, Flink, or Ray - resource tuning, checkpointing, failure recovery.

● Stateful Systems (Must Have): Production experience with Redis (clustering, persistence,

failover) and a solid understanding of operating stateful workloads on Kubernetes

(StatefulSets, PVCs, probes, operators).

● Data Warehouses: Familiarity operating against Snowflake, BigQuery, or similar, and an

understanding of JDBC connectivity and sink reliability.

● Kubernetes & EKS: Strong hands-on EKS cluster creation, scaling, version upgrades, and

operator management.

● Infrastructure as Code: Advanced proficiency with Terraform.

● Programming: Proficiency in Python (or similar) for automation and tooling. Comfort

reading and debugging JVM-based systems is a strong plus.

● Reliability Mindset: Demonstrated ownership of incident management, RCA, capacity

planning, and performance tuning for high-throughput systems.

● CI/CD: Solid understanding of CI/CD methodology (Jenkins, GitHub Actions, or GitLab CI)

for containerized and non-containerized apps. Supporting, not the core of the role.

● Nice to Have: Configuration management (Ansible preferred); broader AWS services

(IAM, VPC, EC2, S3, Lambda); AWS CloudFormation.

● Soft Skills: Excellent communication and organizational skills; ability to coordinate

effectively within a team and with customers.

Why This Might Be Worth It

● You own the hard part. The stateful, distributed systems that move billions of rows are

the platform's most demanding reliability problems - and they'd be yours.

● Impact at scale from day one. Your work keeps mission-critical data flowing for

companies like DoorDash and LinkedIn.

● The AI wave is real for us. We're not bolting AI onto a legacy product. Intelligent

connectors, context-aware data movement, and agentic workflows are the core of what

we're building next - on top of the runtime you'd run. ○ Small team, big problems. Direct

access to the CTO, real influence over product direction, and the autonomy to make

significant technical bets. ○ Recognized platform, startup energy. Enterprise validation

with the speed and ownership of an early-stage company.

Role Summary

Seeking an experienced SQL Developer with strong expertise in Data Lake architecture, Data Engineering, AI/ML data modelling, and Vector Database design. The candidate will be responsible for building scalable data platforms, developing optimized SQL solutions, designing AI-ready data models, and supporting enterprise analytics and GenAI initiatives.

Key Responsibilities

• Design, develop, and optimize complex SQL queries, stored procedures, views, and database objects.
• Build, maintain, and govern enterprise Data Lakes for structured, semi-structured, and unstructured data.
• Design scalable data models for Analytics, Machine Learning (ML), and AI applications.
• Develop and maintain data ingestion, transformation, and data preparation pipelines.
• Architect and manage Vector Database solutions supporting GenAI, semantic search, embeddings, and RAG-based applications.
• Ensure data quality, security, performance, governance, and scalability across platforms.
• Integrate data from multiple enterprise systems, databases, APIs, and business applications.
• Collaborate with Business, Analytics, Data Science, and AI teams to deliver enterprise data solutions.

Mandatory Skills

• Advanced SQL Development (SQL Server, PostgreSQL, Oracle, MySQL, etc.)
• Data Lake Architecture, Development, and Maintenance
• Data Warehousing & Dimensional Data Modelling
• AI/ML Data Modelling and Feature Engineering
• Python for Data Engineering, Data Processing, and Automation
• Query Performance Tuning & Database Optimization
• Data Governance & Data Quality Management
• Vector Database Architecture and Management (Pinecone, Qdrant, Weaviate, Milvus, Chroma, or similar)
• Experience handling large-scale structured and unstructured datasets

Preferred Skills

• Experience with GenAI, RAG (Retrieval-Augmented Generation), Embeddings, and LLM-based applications
• PySpark and Distributed Data Processing
• Power BI or Enterprise Reporting Platforms
• Knowledge of MLOps, AI data pipelines, and modern data architectures

Key Attributes

• Strong analytical and problem-solving skills
• Ability to independently own end-to-end data platform solutions
• Excellent communication and stakeholder management skills
• Passion for Data Engineering, AI, ML, and GenAI technologies

Ideal Candidate

A hands-on SQL Developer who can build and maintain enterprise Data Lakes, design AI/ML-ready data models, develop Python-based data solutions, and architect Vector Database platforms to support advanced analytics, AI, and GenAI initiatives.

Job Title: Automation Engineer – Watermelon Tool 

Experience: 6–7 Years

Location: Bangalore

Work Mode: Hybrid

Notice Period: Immediate Joiners Only

Key Responsibilities:

Design, develop, and maintain automated test scripts using the Watermelon automation tool.

Build and enhance automation frameworks for web, API, and enterprise applications.

Analyze business and functional requirements to identify automation opportunities.

Execute automated regression, smoke, sanity, and functional test suites.

Maintain reusable automation components and improve test coverage.

Integrate automation scripts with CI/CD pipelines.

Perform root cause analysis for failed test cases and provide detailed defect reports.

Work closely with developers, business analysts, and QA teams to resolve issues.

Ensure automation standards, coding best practices, and documentation are followed.

Participate in Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.

Required Skills:

5–10 years of experience in Automation Testing.

Strong hands-on experience with the Watermelon automation tool (mandatory).

Experience in test automation framework development and maintenance.

Knowledge of API testing and automation.

Experience with SQL for database validation.

Familiarity with Git or other version control systems.

Experience with CI/CD tools such as Jenkins, Azure DevOps, or GitLab CI.

Strong understanding of SDLC, STLC, and Agile methodologies.

Excellent debugging, analytical, and problem-solving skills.

Good verbal and written communication skills.

Preferred Skills:

Experience with Selenium, Playwright, Cypress, or similar automation tools.

Knowledge of Java, Python, or JavaScript for automation scripting.

Exposure to cloud platforms such as AWS, Azure, or GCP.

Experience working in enterprise-scale automation projects.

ISTQB or equivalent testing certification is an added advantage.

Roles & Responsibilities:

Develop scalable and maintainable automation solutions.

Improve automation coverage and reduce manual testing effort.

Collaborate with stakeholders to deliver quality software releases.

Identify automation improvements and implement best practices.

Support production validation and release testing activities.

Mandatory Skills:

Watermelon Automation Tool

Test Automation

Automation Framework Development

API Testing

SQL

Git

CI/CD

Agile Methodology

Generative AI Engineer 

Role Overview:

You will be responsible for the hands-on development, coding, and deployment of AI-powered features. Your focus is on writing clean, efficient code to integrate LLMs into our existing tech stack, building robust data pipelines for RAG, and ensuring the reliability of model outputs through rigorous testing and optimization.

Key Responsibilities

• Application Implementation: Code and integrate LLM APIs (OpenAI, Anthropic, etc.) or local models into backend services using Python, FastAPI, etc.,
• MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript) to expose internal databases, APIs, and file systems to AI agents.
• RAG Implementation: Build and maintain the "plumbing" for Retrieval-Augmented Generation—specifically coding the data ingestion scripts, text chunking logic, and metadata filtering.
• Vector DB Management: Perform day-to-day operations on vector databases (Pinecone, Milvus, etc.), including indexing, querying, and optimizing search retrieval.
• Prompt Programming: Develop, version-control, and refine complex prompt templates (using Jinja2 or similar) to ensure consistent structured outputs (JSON/YAML).
• Agent Development: Implement multi-step workflows using LangChain, LangGraph, CrewAI etc.,, focusing on tool-calling logic and error handling.
• Evaluation & Testing: Build automated test suites to detect "hallucinations" and measure accuracy using frameworks.
• Performance Tuning: Implement caching layers and streaming responses to reduce latency and improve the end-user experience; Token optimization.
• Data Pre-processing: Clean and tokenize datasets for model fine-tuning or high-quality context retrieval.

Technical Skills (The "Execution" Stack)

• Language: Advanced Python (Asyncio, Pydantic) and optional TypeScript/Node.js (for full-stack integration).
• AI Frameworks: Hands-on experience with any of LangChain, LlamaIndex, and Hugging Face Transformers. RAG and Vector search concepts.
• Data Handling: Proficiency in SQL and handling unstructured data formats (PDFs, Markdown, JSON).
• Deployment: Practical experience with Docker, GitHub Actions (CI/CD), and experience with OpenTelemetry, LangSmith, Weights & Biases etc., Understanding of evaluation/guardrails.
• MCP/API Proficiency: Deep understanding of RESTful APIs, Streaming HTTP, MCP server vs client, JSONRPC

EGNYTE YOUR CAREER. SPARK YOUR PASSION.

Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 23,000+ customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career, you become part of a team of Egnyters that are doers, thinkers, and collaborators who embrace and live by our values:

Invested Relationships

Fiscal Prudence

Candid Conversations

ABOUT EGNYTE

Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 23,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere.

ABOUT THE ROLE

We are seeking a skilled Mid-Level Python Developer & Test Automation Engineer with 3 to 5 years of experience. In this dual role, you will design and develop robust backend systems while building scalable, automated testing frameworks for both UI and backend application. You will bridge the gap between development and quality assurance, ensuring our software is both highly functional and rigorously tested.

WHAT YOU’LL DO:

• Backend Development: Design, write, and maintain clean, scalable Python code for backend services and microservices.
• API Engineering: Build, integrate, and document secure RESTful or GraphQL APIs.
• Automation Frameworks: Design and maintain UI/Backend automated testing suites for unit, integration, and end-to-end testing.
• CI/CD Integration: Integrate automated test scripts into DevOps pipelines to enable continuous deployment.
• Bug Detection: Identify, log, and track software defects while collaborating with teams to resolve them quickly.
• Code Quality: Participate in code reviews to enforce PEP 8 standards, maintainability, and security best practices.

YOUR QUALIFICATIONS:

• Python Expertise: 3+ years of professional software development experience using core Python and Object-Oriented Programming (OOP).
• Web Frameworks: Hands-on experience with at least one major Python web framework (FastAPI, Django, or Flask).
• Testing Frameworks: Strong proficiency with automated testing tools like pytest, unittest, Selenium. Knowledge in Playwright is nice to have.
• AI assisted testing tools/frameworks: Nice to have experience with AI assisted testing tools or framework.
• Database Management: Solid experience writing complex queries for relational (PostgreSQL, MySQL) or NoSQL (MongoDB) databases.
• DevOps & Tools: Proficient with Git version control and CI/CD platforms like Jenkins, GitHub Actions, or GitLab CI.
• Agile Methodology: Experience working in an Agile/Scrum environment with tools like Jira or Confluence. 

Preferred Qualifications

• Experience with containerization technologies like Docker and Kubernetes.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Performance and Load Testing tools like Locust or JMeter

BENEFITS

• Competitive salaries
• Medical insurance and healthcare benefits for you and your family
• Fully paid premiums for life insurance
• Flexible hours and PTO
• Gym reimbursement
• Childcare reimbursement
• Group term life insurance

EQUAL EMPLOYMENT OPPORTUNITY

At Egnyte, we celebrate our unique differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Our global Egnyte Employee Communities (EECs) support representation and inclusion across our diverse workplace. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.

Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy.

EGNYTE YOUR CAREER. SPARK YOUR PASSION.

Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 23,000 customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career; you become part of a team of Egnyters who are doers, thinkers, and collaborators who embrace and live by our values:

Invested Relationships

Fiscal Prudence

Candid Conversations

ABOUT EGNYTE

Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 23,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere.

WHAT YOU’LL DO: 

• Fine-tune and train SLMs using Hugging Face, TRL, and adapter methods (LoRA, QLoRA, PEFT)
• Optimize models for inference via quantization, pruning, and knowledge distillation
• Deploy models to edge devices, mobile, and local servers with strict latency targets
• Build end-to-end MLOps pipelines from data ingestion to deployment
• Monitor model accuracy, latency, and hardware utilization in production
• Evaluate model quality using benchmarking frameworks and custom evaluation suites

YOUR QUALIFICATIONS:

• SLM Development & Fine-tuning: Train and fine-tune SLMs using Hugging Face and Knowledge on Adaptors.
• Model Optimization: Apply quantization, pruning, knowledge distillation, and optimization for lightweight, efficient models.
• Edge Deployment: Deploy models to edge devices, mobile, and local servers, etc.
• Pipeline Engineering: Build end-to-end MLOps pipelines — from data ingestion to deployment.
• Performance Monitoring: Track model accuracy, latency, and CPU/GPU usage in production.

Good to have

• Deployment experience on edge or mobile environments
• Knowledge of ONNX export and cross-platform inference
• MLOps tooling — experiment tracking, model registries, CI/CD for ML

EQUAL EMPLOYMENT OPPORTUNITY

At Egnyte, we celebrate our unique differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Our global Egnyte Employee Communities (EECs) support representation and inclusion across our diverse workplace. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.

Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy.

Job Title : MLOps Engineer

Mode: Hybrid

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary:

We are looking for a skilled and proactive ML Engineer with strong expertise in Python, Databricks, and Machine Learning model development. The ideal candidate should be proficient in building scalable data pipelines and deploying ML models, with a working knowledge of MLOps principles and tooling. This role offers an opportunity to work on impactful AI/ML initiatives in a collaborative environment.

Key Responsibilities:

• Develop and maintain machine learning pipelines for training, testing, and deploying models

• Design and implement infrastructure for managing and monitoring machine learning models

• Work with data scientists to build scalable, efficient, and automated model training and testing processes

• Collaborate with software engineers to integrate machine learning models into production systems

• Automate and optimize the deployment and scaling of machine learning models in a distributed computing environment

• Monitor and troubleshoot machine learning systems and infrastructure to ensure high availability and performance

• Develop and maintain documentation and best practices for MLOps processes and procedures.

Experience:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

• 3+ years of experience in MLOps or related field, including building and deploying machine learning models at scale

•Proficiency in programming languages such as Python, Java, and C++

•Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras

• Experience with containerization technologies such as Docker and Kubernetes

• Strong understanding of DevOps principles and practices

• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud

About the Programme 

Developing an enterprise AI platform focused on financial compliance and intelligence.  

Role Overview 

We are looking for a strong Data Engineer to own the data foundation of the platform. Every model, every AI output, and every compliance decision the system makes depends on data arriving reliably, completely, and on time. You will design and build the ingestion pipelines from all source systems into the data platform, own the pipeline monitoring infrastructure, and work closely with internal IT and operations teams to extract data from complex enterprise source 

systems.  

Key Responsibilities 

Data Discovery & Audit 

• Conduct a thorough data audit with internal IT and operations teams — map every data 

source needed for the platform, assess what already exists on the data platform, and identify gaps. 

• Document data sources, schemas, update frequencies, and quality issues for all relevant datasets  

• Raise data gaps and quality risks to the Solutions Architect  

Pipeline Design & Build 

• Design and build ingestion pipelines from all source systems — ERP, government portals, supplier portals, and banking feeds — into the data platform. 

• Design pipelines for both batch and real-time ingestion patterns 

• Ensure pipelines are idempotent, resumable, and handle source system failures gracefully without data loss or duplication. 

Data Quality & Reliability 

• Build pipeline monitoring and alerting so data failures are caught and flagged before they corrupt model training or inference. 

• Define and implement data quality checks at the point of ingestion — schema validation, completeness checks, and anomaly detection on incoming data volumes. 

• Maintain clear data lineage so the team always knows where a data point came from and when it was last updated. 

Collaboration & Handoff 

• Work closely with internal IT and automation team who hold institutional knowledge of the source systems — this is not a solo exercise. 

• Hand off clean, well-documented datasets to the ML Engineers and LLM Engineer for model training and knowledge base building. 

• Support the MLOps Engineer in ensuring production pipelines are stable and monitored post-deployment. 

Required Qualifications 

Education 

•B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field. 

Experience 

• 5+ years of data engineering experience with at least 2 years working on production pipelines at enterprise scale. 

• Demonstrated experience building pipelines from complex enterprise source systems — ERP or equivalent. 

• Experience building both batch and real-time / streaming ingestion pipelines. 

Technical Skills 

• Languages: Python and PySpark; SQL proficiency essential. 

• Data Platform: Databricks and Delta Lake — must have hands-on production experience. 

• Pipeline Orchestration: Apache Airflow, Databricks Workflows, or equivalent. 

• Streaming: Kafka, Spark Structured Streaming, or equivalent for real-time ingestion patterns. 

• ERP Integration: Experience extracting data from SAP or equivalent large ERP systems strongly preferred. 

• API Integration: REST API consumption for government portal or third-party data feeds. 

• Data Quality: Experience with data quality frameworks — Great Expectations or equivalent. 

• Observability: Pipeline monitoring, alerting, and data lineage tooling. 

Preferred Qualifications 

• Familiarity with SAP data models  

• Prior experience with government API ecosystems — GSTN, ICEGATE, or similar. 

• Experience building pipelines that feed ML model training workflows. 

• Exposure to Unity Catalog or similar data catalogue and governance tools. 

• Prior work in fintech, compliance, or tax technology environments. 

We are seeking Senior Backend Engineers who can hack around multiple technologies and build highly scalable, low-latency, distributed systems with RESTful services. You will be responsible for developing new software products (internal) and solving complex technical challenges for scale-ups and enterprise companies. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills.

You’ll be responsible for—

• Writing clean, high-quality, high-performance, and maintainable code.
• Solving complex technical problems.
• Performing an objective analysis of the problem statement and coming up with an unbiased technical solution before writing a single line of code.
• Coordinating cross-functionally to ensure the project meets business objectives and compliance standards.
• Participating in and driving code reviews.
• Building robust, secure, and scalable microservices.
• Implementing RESTful services with a metric-driven API Gateway.
• Ensuring sub-second server response and will be responsible for implementing relational, document, key, object, or graph data stores, index stores and messaging stores as needed.
• Tracking defects and work with business owners and users to triage bugs and manage backlog
• Taking ownership to run and maintain Cloud infrastructure.
• Evaluating relevant technologies, influencing and driving architecture and design discussions.
• Architecting & designing the platform.
• Mentoring junior engineers helping them grow, performing code reviews, system monitoring & delegation.
• Writing documentation & create engineering processes.
• Working as an individual contributor.
• Helping drive KPIs with Product.
• Taking ownership of backend systems.
• Helping with unit tests & QA process.
• Scaling the engineering team.
• System scaling to hundreds of millions of users.
• Working with product managers and designs.

Requirements

What you need—

• Overall 5-8 years of experience in software development with a strong base in Golang/Java/Python and a degree in Computer Science(optional).
• Experience with Go, K8, Docker, AWS, and CI/CD.
• Experience with micro web frameworks – like Springboot, Gin/Mux.
• Experience in working with microservice architectures, Transactional systems, and Distributed environments.
• Exposure to building RESTful APIs with monitoring, fault tolerance, and metrics (with something like Hystrix).
• Experience with MySQL, and NoSQL (Cassandra, Redis, DynamoDB).
• Experience in server-side services using ElasticSearch and ESB - Camel, ActiveMQ.
• DevOps experience.
• Experience with AWS stack.
• Excellent attention to detail.
• Outstanding written and verbal communication skills.
• To be a self-starter who can work well with minimal to no guidance in a fluid environment.
• To be excited by challenges surrounding the development of highly scalable & distributed systems.
• To be agile and able to adapt quickly to changing requirements scope and priorities.
• To be experienced in working on massively large-scale data systems in production environments.
• To have led or mentored an engineering team before(optional).
• To have contributed to open-source projects.
• To have a strong drive & desire for continued growth.
• Proficiency in English.
• Experience with Web3(optional).

Benefits

What you get—

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

Job Title: Senior Data Tester

Location : Hyderabad

Mode: Hybrid

Notice Period: Immediate Joiner

Key Responsibilities:

• 8+ years of experience in ETL/data testing.
• Design, implement, and execute data validation test plans and test cases.
• Understanding of data modelling and data governance principles.
• Experience with test automation frameworks and scripting (e.g., Python, Shell)Conduct thorough ETL testing, including data extraction, transformation, and loading.
• Validate data integrity across various sources and destinations (data lakes, warehouses, etc.)
• Perform data reconciliation and analysis to identify inconsistencies or data quality issues.
• Develop and maintain automated data testing frameworks using SQL or scripting languages.
• Strong experience with SQL and writing complex queries for data validation.
• Knowledge of data warehouse concepts and testing tools. Experience with ETL tools (e.g., Informatica, Talend, SSIS, etc.)
• Familiarity with cloud platforms (Azure, GCP) and modern data tools (e.g., Snowflake, Big Query).
• GCP is mandatory. Experience in Agile development and working within cross-functional teams.
• Exposure to BI tools (Power BI, Tableau, Looker)
• Familiarity with CI/CD pipelines and version control systems like Git ISTQB or equivalent testing certifications.

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
• Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
• Work with cloud platforms GCP, Azure to manage data infrastructure.
• GCP as mandatory skills
• Collaborate with analytics and product teams to understand data needs and deliver solutions.
• Ensure data quality, reliability, security, and compliance across all data systems.
• Mentor junior data engineers and contribute to best practices and code reviews.
• Monitor and troubleshoot data pipeline performance and resolve data-related issues.
• Automate data validation, monitoring, and alerting processes.
• 8+ years of experience in data engineering or software engineering with a data focus.
• Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
• Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of data modeling, data lakes, and ETL/ELT design.
• Hands-on experience with orchestration tools like Airflow, dbt, or similar.
• Solid experience with cloud data platforms (AWS/GCP/Azure).
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
• Experience working in a DevOps or DataOps environment.
• Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
• Experience supporting machine learning workflows and data science initiatives.

Full Stack Developer

Experience: 3 to 5 Years

Location: Hyderabad

Interview Mode: Face-to-Face (F2F)

Work Mode: Hybrid

Employment Type: Full-Time

Note: Immediate joiners or candidates with a notice period of up to 15 days are preferred. We are only considering candidates who can attend a face-to-face interview at our office.

Role Summary;

We are looking for a Full Stack Developer (React.js + Python + AWS + AI) to design, develop, and maintain scalable web applications and AI-powered solutions. The ideal candidate must have strong experience in React.js, Python, AWS, and AI development. Hands-on AI development experience is mandatory for this role.

Mandatory AI Skill Requirement - AI development experience is mandatory. Candidates without hands-on AI development experience will not be considered.

Candidates must have practical experience in one or more of the following:

• Building AI-powered applications.
• Working with Large Language Models (LLMs).
• Prompt Engineering.
• Retrieval-Augmented Generation (RAG).
• AI agent development using LangChain, LangGraph, or similar frameworks.
• Integrating AI models through APIs such as OpenAI, Anthropic, or Gemini.
• Developing AI-enabled workflows and intelligent business applications.

Note: Experience using AI coding assistants (ChatGPT, GitHub Copilot, Claude, Gemini, etc.) alone does not meet this requirement. Candidates must have actual AI application development experience.

Key Responsibilities

• Develop and maintain full-stack web applications.
• Build responsive frontend applications using React.js.
• Develop backend REST APIs using Python (FastAPI / Django / Flask).
• Design, develop, and integrate AI-powered features into applications.
• Develop and deploy applications on AWS cloud services.
• Work with relational databases (MySQL / PostgreSQL / SQL Server).
• Integrate frontend and backend components.
• Follow Agile/Scrum development processes.
• Write clean, maintainable, and production-ready code.
• Collaborate with cross-functional teams to deliver scalable and high-quality solutions.

Required Skills (Mandatory)

• 3 to 5 years of Full Stack development experience.
• Strong experience in React.js.
• Strong backend development experience in Python.
• Hands-on experience with AWS cloud services.
• Hands-on AI development experience (Mandatory).
• Experience with LLMs, Prompt Engineering, RAG, LangChain, LangGraph, or similar AI frameworks.
• REST API development experience.
• Strong SQL database experience.
• Git and Agile development workflow.
• Good understanding of software design principles and best practices.

Good to Have

• Docker
• CI/CD pipelines
• Microservices architecture
• Kubernetes
• Experience with vector databases and AI model integrations

Preferred Qualifications

• Bachelor's degree in Computer Science or a related field.
• Strong problem-solving and analytical skills.
• Good communication and teamwork abilities.
• Passion for learning new technologies, especially AI, cloud technologies, and modern software development.

Job Description:

We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and Python programming.

You will work closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models and integrate generative AI solutions into existing workflows.

Your responsibilities will include:

• Collaborating with cross-functional teams to design and deliver high-performance AI models, including NLP, computer vision, semantics engines, linguistic analysis, risk management, and time-series prediction models. Integrating generative AI solutions into existing workflow systems.
• Developing and maintaining the ML Operations CI/CD pipeline for seamless deployment and monitoring. Training, tuning, and optimizing AI models and algorithms for enhanced performance.
• Implementing complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.
• Creating ML/AI models for business teams and establishing metrics to track their accuracy and performance. Overseeing the full lifecycle of algorithm development, from ideation to deployment and monitoring. Evaluating and ranking ML algorithms based on their potential success in solving specific problems.
• Serving as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.

Required Experience and Skills:

Machine Learning:

• Proficient in generative AI techniques, prompt engineering, and Retrieval-Augmented Generation (RAG) (3+ years).
• Experience with Large Language Models (LLMs) such as OpenAI, Gemini, LLAMA, and other state-of-the-art models (3+ years).
• Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow, Keras, BERT, LayoutLM, and traditional ML algorithms (5+ years).
• Experience with distributed ML/AI training libraries/models: Koalas, Horovod, DDP.

Python Programming and Software Engineering:

• Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (5+ years).
• Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).
• Proficient in software design concepts focusing on cohesion and coupling (2+ years). Knowledge of SOLID principles (2+ years).

Education and Experience:

• Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.
• At least 5 years of experience as a software engineer and 5 years of ML-related programming.

Job Description:

Position: Senior Data Engineer

Location: Chennai / Pune / Bangalore / Hyderabad

Working Type: WFO

Shift: UK Shift (2:00 – 11:00 PM)

Experience : 7+ years overall

Interviews: Assessment || 2 Interview rounds.

Notice Period: Immediate Joiner

Key Responsibilities

Implement ingestion, transformation, and optimization of enterprise data sources into Microsoft Fabric Lakehouse environments.

Configure and optimize Fivetran connectors (Oracle, SQL DB, etc.)

Manage large-volume ingestion and backfill operations

Implement Bronze to Silver transformation pipelines

Develop incremental load and CDC logic

Optimize Lakehouse performance and storage patterns

Implement monitoring (record counts, load duration, failure tracking)

Support Dev/Test/Prod promotion processes

Required Qualifications

7+ years of data engineering experience

Hands-on experience with Microsoft Fabric or Azure Synapse/Data Factory

Strong experience with Fivetran or similar ELT tools

Experience handling high-volume datasets (hundreds of millions of records)

Proficiency in SQL, Python, and data modeling concepts

Strong understanding of Medallion architecture.

Location: Ahmedabad / WFO

Experience: 0–1 Year / Freshers

Internship: 6months ( leading to full-time employment )

About the Role

We are looking for a motivated DevOps Engineer Intern who is interested in Cloud, Automation, and Infrastructure. You will work with our engineering team on application deployments, cloud environments, CI/CD pipelines, and day-to-day DevOps activities.

What You'll Work On

• Work with Linux-based systems and perform basic troubleshooting.
• Use Git & GitHub for version control and team collaboration.
• Write basic Bash/Shell scripts to automate repetitive tasks.
• Work with Docker to build and run containerized applications.
• Assist with CI/CD pipelines and automated application deployments.
• Gain hands-on exposure to AWS, Azure, or GCP.
• Understand basic cloud networking, IAM, and security concepts.
• Troubleshoot deployment, application, and infrastructure issues.
• Maintain basic technical documentation and follow DevOps best practices.

Must-Have Skills

• Basic understanding of Linux.
• Hands-on knowledge of Git & GitHub.
• Basic Bash/Shell scripting.
• Understanding of Docker and containers.
• Basic understanding of at least one cloud platform (AWS/Azure/GCP).
• Understanding of CI/CD concepts.
• Basic networking concepts, including HTTP/HTTPS, DNS, ports, IP, and SSH.
• Good troubleshooting and problem-solving skills.
• Strong interest in DevOps, Cloud, and Automation.

Good to Have

• Hands-on experience with GitHub Actions.
• Basic knowledge of Terraform.
• Exposure to Kubernetes.
• Basic Python scripting.
• Personal DevOps/Cloud projects or a GitHub portfolio.
• AWS/Azure/GCP or DevOps certification.

About the Programme

Developing an enterprise AI platform focused on financial compliance and intelligence

Role Overview

We are looking for a QA Engineer to own testing across the full platform. In a compliance context, a software defect is not just a technical issue — it carries real financial and regulatory consequences. You will be involved from the earliest stages of development, defining acceptance criteria, building test frameworks, and ensuring that every component of the system meets the accuracy and reliability standards required before it goes near a production compliance workflow.

Key Responsibilities

Test Strategy & Planning

•       Develop and own the overall test strategy for the platform, covering all layers — data pipelines, ML models, APIs, application services, and frontend interfaces.

•       Work with the Product Manager to define acceptance criteria for every user story before development begins, not after.

•       Define accuracy and reliability thresholds for each ML model in scope — what performance levels are required before a model is considered production-ready.

•       Maintain a living test plan that evolves with the product as new use cases are added.

Functional & Business Logic Testing

•       Translate compliance rules and business logic into structured, executable test cases.

•       Work closely with the subject matter experts to identify edge cases and exception scenarios that automated tests must cover.

•       Validate that AI outputs — channel routing decisions, classification recommendations, and generated responses — are correct against defined compliance ground truth.

•       Test end-to-end workflows from data ingestion through to user-facing outputs, ensuring correctness at every stage.

ML & AI System Testing

•       Build regression test suites for all deployed models so that retraining does not break existing correct behaviours.

•       Test model outputs for consistency, groundedness, and accuracy using both automated evaluation and structured manual review.

•       Validate fallback mechanisms — ensure the system behaves correctly when model confidence is low or an upstream service is unavailable.

•       Test feedback loop integrity — verify that validator decisions are correctly captured and routed to the model retraining pipeline.

API & Integration Testing

•       Build and maintain API test suites for all integration endpoints — covering correctness, error handling, and edge cases.

•       Perform load and performance testing on real-time inference endpoints to validate behaviour under expected production volumes.

•       Test all third-party and government portal integrations against documented API contracts, including failure and retry scenarios.

User Acceptance & Production Readiness

•       Coordinate and facilitate user acceptance testing with the RIL compliance and assurance teams.

•       Produce a formal production readiness assessment before each deployment, documenting what has been tested, what passed, and any known residual risks.

•       Monitor for defects in production and manage the defect lifecycle through to resolution.

Required Qualifications

Education

•       B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field.

Experience

•       4+ years of QA engineering experience with at least 2 years testing AI, ML, or data-heavy systems in production.

•       Experience writing and maintaining automated test frameworks, not just manual testing.

•       Demonstrated ability to translate complex business rules into structured test cases.

Technical Skills

•       Test Automation: Pytest, Selenium, Playwright, or equivalent for backend and frontend automation.

•       API Testing: Postman, REST-assured, or equivalent; experience with contract testing.

•       Performance Testing: Locust, JMeter, or equivalent for load and stress testing.

•       ML Testing: Experience validating ML model outputs, building evaluation datasets, and running regression suites against retrained models.

•       Data Testing: Experience validating data pipeline outputs — schema checks, completeness, and consistency.

•       Languages: Python for test scripting and automation.

•       CI Integration: Experience integrating test suites into CI/CD pipelines for automated test execution.

Preferred Qualifications

•       Prior experience testing compliance, fintech, or legal technology systems where business logic accuracy is critical.

•       Familiarity with LLM evaluation frameworks — RAGAS, TruLens, or equivalent.

•       Experience with exploratory testing techniques for AI systems where outputs are probabilistic.

•       Prior exposure to regulated environments where formal sign-off and test documentation are required.

* Strong practical knowledge and interest in modern AI tools.

* Genuine curiosity and willingness to continuously learn.

* Ability to research, experiment, implement, troubleshoot and improve independently.

* Good understanding of prompting and AI workflows.

* Strong problem-solving mindset.

* Basic understanding of APIs, integrations and automation.

* Ability to explain technology clearly to non-technical people.

* Comfortable using AI to solve real-world business problems.

Hiring for Data Analyst

Exp : 5 - 7 yrs

Edu : BE/B.Tech

Work Location : Noida WFO

Skills :

Expertise in SQL Server, including database design, performance tuning, query optimization, and security.

Hands-on experience developing ETL solutions using SSIS, Azure Data Factory (ADF), and Python.

About the Programme

Developing an enterprise AI platform focused on financial compliance and intelligence.

Role Overview

We are looking for a Backend Engineer to own the integration layer of the platform. You will build the APIs and services that connect AI outputs back into operational workflows, integrate with government portals and external data sources, and ensure that the system interacts reliably with RIL’s existing infrastructure. This role requires equal measures of technical rigour and pragmatism to deliver reliably within a fast-moving build timeline.

Key Responsibilities

Integration Mapping & Design

•       Work with the Solutions Architect to map every integration touchpoint — ERP workflow interfaces, government portals, supplier portals, and banking feeds.

•       Understand the latency requirements for each integration and design accordingly — real-time endpoints and batch integrations have fundamentally different design constraints.

•       Design robust fallback mechanisms for every integration — if the AI model is unavailable or low-confidence, the system must degrade gracefully without blocking operational workflows.

Real-Time API Development

•       Design and implement the API layer that connects the AI inference layer to operational systems — clean contracts, versioned endpoints, and clear error responses.

•       Ensure all real-time integrations are built with resilience patterns — circuit breakers, retry logic, timeouts, and graceful degradation under load.

Government Portal & External Integrations

•       Build integrations with government portal APIs for inward supply data, vendor return filing status, and notice data where available via official channels.

•       Build the integration with the customs data portal

•       Manage the specific constraints of government API ecosystems — rate limits, authentication flows, schema changes, and reliability issues that differ significantly from commercial APIs.

Monitoring & Production Stability

•       Build API monitoring and alerting covering latency, error rates, and upstream availability so integration failures are caught before they affect the compliance team.

•       Work with the MLOps Engineer to ensure model inference endpoints are stable and performant enough for the real-time integration to depend on.

•       Maintain clear API documentation so the Full Stack Engineer and other squad members can consume integrations without dependency.

Required Qualifications

Education

•       B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field.

Experience

•       5+ years of backend engineering experience with a focus on API design and enterprise system integration.

•       Proven experience building and maintaining production-grade integrations with complex or legacy enterprise systems.

•       Experience with real-time, latency-sensitive API development in an operational context.

Technical Skills

•       Languages: Python (primary); working knowledge of at least one of Java, Go, or Node.js.

•       API Design: REST API design principles, versioning, authentication (OAuth 2.0, API keys, mTLS), and contract-first development.

•       Resilience Patterns: Circuit breakers, retry logic, rate limiting, bulkheads, and graceful degradation.

•       ERP Integration: Experience integrating with SAP or equivalent large ERP systems — BAPIs, RFC calls, or event-driven extraction patterns strongly preferred.

•       Async & Messaging: Kafka, RabbitMQ, or equivalent for event-driven integration patterns.

•       Containerisation: Docker and Kubernetes for deploying and managing API services.

•       Observability: API monitoring, distributed tracing (Jaeger, Zipkin, or equivalent), and structured logging.

Preferred Qualifications

•       Prior experience with government API ecosystems — GSTN, ICEGATE, or similar; understanding of their specific constraints and reliability characteristics.

•       Experience building integrations that serve ML model inference endpoints in a production setting.

•       Familiarity with SAP integration patterns — SAP BTP, OData services, or SAP API Hub.

•       Prior work in fintech, compliance, legal technology, or similarly regulated environments.

•       Experience with API gateway tooling — Kong, AWS API Gateway, or equivalent.

Strong Azure Databricks Engineer / Senior Data Engineer Profile

2

Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3

Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4

Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5

Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6

Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7

Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8

Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9

Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10

Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

Roles & Responsibilities

• Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration

of enterprise-wide data from diverse sources

• Build and optimize data engineering workflows using Databricks and PySpark

• Write efficient, high-performance SQL for data transformation and analysis

• Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing,

data models, and pipelines

• Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the

development lifecycle

• Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production

environments with proper change control processes

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions

• Ensure data quality, reliability, and performance across all pipelines and platforms

Ideal Candidate

1Strong Azure Databricks Engineer / Senior Data Engineer Profile

2Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

About the company

The client is building an AI-native platform for modern law firms.

Legal work is evolving rapidly, but much of the industry's workflow continues to rely on fragmented software and manual processes. The team is building an intelligent platform that helps law firms streamline work across the entire legal lifecycle, including document screening, drafting, filing, research, compliance, and other high-value legal workflows.

Their founding team combines deep expertise across both law and technology, giving us a unique perspective on how AI can fundamentally reshape legal operations while maintaining the precision and reliability that the profession demands.

We're looking for engineers who want to build products from first principles, move quickly, and help define the future of AI in legal technology.

About the role

We're hiring a Lead Engineer to help build the core platform from the ground up.

This is a high-ownership role. You'll work across backend systems, AI infrastructure, product architecture, and deployment, collaborating directly with the founders to design and ship features that reach customers quickly.

If you enjoy solving hard engineering problems, shipping fast, and working in a small, ambitious team, we'd like to talk.

What You'll Build

• AI-powered legal workflows for law firms
• Agentic systems for drafting, screening, and legal document analysis
• Reliable backend services and APIs
• Retrieval and knowledge systems for legal intelligence
• Evaluation pipelines to improve AI quality and reliability
• Internal developer tooling and scalable platform infrastructure

What We're Looking For

• Around 5 years or more of software engineering experience
• Strong Proficiency in at least one backend language: Python (FastAPI or Django), or Node.js
• Experience working with at least one database: MongoDB, PostgreSQL, MySQL, or another relational database
• Understanding of modern AI application architecture, including concepts such as: Agentic systems AI SDKs Retrieval-Augmented Generation (RAG) Prompt engineering Evaluation frameworks (Evals)
• Strong system design and problem-solving skills
• Ability to ship production-quality software quickly
• High ownership and bias toward execution
• Comfortable learning new technologies as the product evolves

Nice to Have

• Experience building products in Compliance, FinTech, RegTech, or LegalTech
• Experience deploying and operating AI-powered production systems
• Familiarity with cloud platforms and modern deployment workflows
• Experience working in an early-stage startup
• Experience leading teams or mentoring people

What We Value

• High agency
• Strong engineering fundamentals
• Curiosity and continuous learning
• Fast execution without compromising quality
• Clear communication and collaborative problem solving

Why Join Us

• You'll be joining at the earliest stage of the company and will help shape both the product and the engineering culture.
• This is an opportunity to work directly with founders who combine legal and technical expertise, solve meaningful problems for the legal industry, and build AI systems that are used every day by legal professionals.
• If building from zero excites you more than maintaining legacy systems, we'd love to hear from you

Hiring : Senior Databricks AI Architect

Exp : 15 - 18 yrs

Work Location : Pune WFO

Skills :

10 +years of experience in Data Engineering, Data Architecture, Analytics, or Software Engineering.

Minimum 5 years of hands-on experience with Databricks (Mandatory).

Strong expertise in designing and implementing enterprise-scale data platforms on Databricks.

Hands-on experience with AI-powered engineering tools such as Databricks Genie, Cursor, GitHub Copilot, or similar AI platforms.

Strong proficiency in Python, SQL, Spark, Delta Lake, and Databricks notebooks.

Excellent communication, stakeholder management

Location: Hyderabad, India (home base), deployed at client sites in India. Occasional Middle East exposure possible.

About the Role

You will work as a senior AI engineer who embeds inside a customer's business. Your job is to learn how the business makes money, find the highest value problem, and build a working system that solves it.

Four behaviors define this role:

1. Go where the work happens. You work onsite with the customer, in the room where decisions are made.
2. Show working software early. You build a prototype in days, not a document in weeks.
3. One person owns the outcome. You are the single point of accountability for the result.
4. Stay after go-live. You keep running and improving the system after launch.

You are the single point of accountability. You are not a solo builder. A full KnackLabs engineering team in Hyderabad builds and runs the production systems behind you.

This role involves extended onsite deployments at client locations in other cities, sometimes up to six months at a stretch. Please apply only if you are ready for this way of working.

What you'll own

1. Discovery - Learn how the customer makes money. Find the highest value problem to solve first.
2. The prototype - Build a working prototype fast, using real or sample data, to prove the idea.
3. The roadmap - Decide what to build, in what order, and set clear success measures tied to business outcomes.
4. The build - Design and ship the production system with the Hyderabad engineering team. This includes data integration, agents, retrieval, and evaluations.
5. The client relationship - Be the trusted technical contact for the customer, from engineers to senior leaders.
6. Go live and after - Deploy the system, watch how it performs, fix problems, and improve it over time.
7. Feedback to the product - Share what you learn in the field so the vendor's product and our internal tools get better.

What we are looking for

1. Around 4 or more years of software engineering experience, including customer-facing or client delivery work.
2. Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.
3. A full-stack development experience with strength in backend technologies.
4. Production experience with large language models, including prompt engineering and agent development.
5. You build with AI coding tools like Claude Code or Codex as your default way of working, and you have shipped real apps or agents this way.
6. Experience building retrieval-augmented generation (RAG) systems: chunking, embeddings, vector databases, retrieval, and reranking.
7. Experience building and deploying AI systems.
8. Experience integrating with APIs and enterprise systems.
9. Experience with at least one cloud platform (AWS, Azure, or GCP).
10. Clear communication. You can explain a technical choice to an engineer and to a business leader.
11. High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a plan.
12. Willingness to work onsite at client locations in India for extended periods, and to travel as the work needs.

Nice to have

1. Experience with on-premises or private cloud (VPC) deployments.
2. Experience with observability and tracing tools such as LangSmith or Braintrust.
3. Experience with data engineering and pipelines.
4. A history of side projects, open source contributions, or products you shipped end-to-end.
5. Experience in embedded or forward-deployed roles before.
6. Experience working at a consulting or professional services firm in a client-facing delivery role.

Stack and tools

1. Languages: Python and TypeScript.
2. Models: Claude and other frontier or open-source models, chosen to fit the customer.
3. AI patterns: RAG, agents, prompt engineering, and evaluations.
4. Vector and retrieval: vector databases and retrieval pipelines.
5. Cloud: AWS, Azure, or GCP, on public or private cloud.
6. Integration: REST APIs and enterprise system connectors.

Location: Hyderabad, India (home base), deployed at client sites in India. Occasional Middle East exposure possible.

About the Role

You will work as a senior AI consultant who embeds inside a customer's business. Your job is to learn how the business makes money, find the highest value problem, and build a working system that solves it.

You will not hand over a document and walk away. You will show working software early, own the roadmap, own the client relationship, and stay after go-live to run and improve the system.

Four behaviors define this role:

1. Go where the work happens. You work onsite with the customer, in the room where decisions are made.
2. Show working software early. You build a prototype in days, not a document in weeks.
3. One person owns the outcome. You are the single point of accountability for the result.
4. Stay after go-live. You keep running and improving the system after launch.

You are the single point of accountability. You are not a solo builder. A full KnackLabs engineering team in Hyderabad builds and runs the production systems behind you.

This role involves extended onsite deployments at client locations in other cities, sometimes up to six months at a stretch. Please apply only if you are ready for this way of working.

What you'll own

1. Discovery - Learn how the customer makes money. Find the highest value problem to solve first.
2. The prototype - Build a working prototype fast, using real or sample data, to prove the idea.
3. The roadmap - Decide what to build, in what order, and set clear success measures tied to business outcomes.
4. The build - Design and ship the production system with the Hyderabad engineering team. This includes data integration, agents, retrieval, and evaluations.
5. The client relationship - Be the trusted technical contact for the customer, from engineers to senior leaders.
6. Go live and after - Deploy the system, watch how it performs, fix problems, and improve it over time.
7. Feedback to the product - Share what you learn in the field so our platform and internal tools get better.

What we are looking for

1. Around 7 or more years of software engineering experience, including customer-facing or client delivery work.
2. Experience working at a consulting or professional services firm in a client-facing delivery role.
3. A full-stack development experience with strength in backend technologies.
4. Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.
5. Production experience with large language models, including prompt engineering and agent development.
6. You build with AI coding tools like Claude Code as your default way of working. You have built real apps and agents this way, not just used it for document generation or review.
7. Experience building retrieval-augmented generation (RAG) systems: chunking, embeddings, vector databases, retrieval, and reranking.
8. Experience building and deploying AI systems.
9. Experience integrating with APIs and enterprise systems.
10. Experience with at least one cloud platform (AWS, Azure, or GCP).
11. Experience building evaluations to measure accuracy, safety, latency, and cost.
12. Clear communication. You can explain a technical choice to an engineer and to a business leader.
13. High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a plan.
14. Willingness to work onsite at client locations in India for extended periods, and to travel as the work needs.

Nice to have

1. Experience deploying AI systems in regulated industries such as insurance, banking, or the public sector.
2. Experience with on-premises or private cloud (VPC) deployments.
3. Experience with observability and tracing tools such as LangSmith or Braintrust.
4. Experience with data engineering and pipelines.
5. A history of side projects, open source contributions, or products you shipped end-to-end.
6. Experience in embedded or forward-deployed roles before.

Stack and tools

1. Languages: Python and TypeScript.
2. Models: Claude and other frontier or open source models, chosen to fit the customer.
3. AI patterns: RAG, agents, prompt engineering, and evaluations.
4. Vector and retrieval: vector databases and retrieval pipelines.
5. Cloud: AWS, Azure, or GCP, on public or private cloud.
6. Integration: REST APIs and enterprise system connectors.

Experience: 4–6 Years

Domain: Automotive IoT | Connected Vehicles | Firmware & OTA

Core Stack: Rust | AWS | IoT Core | Apache Kafka | MemoryDB

Key Responsibilities  

OTA & Firmware Lifecycle  

• Co-own OTA firmware rollout operations across multi-ECU connected vehicle architectures.
• Design automated mechanisms to detect update failures, network interruptions, verification errors, and stalled deployments.
• Implement deterministic retry, recovery, and rollback mechanisms to ensure reliable firmware updates without vehicle bricking.
• Ensure firmware package integrity, signature validation, and data security throughout the OTA pipeline.

Data Engineering & Telemetry  

• Design and maintain real-time streaming pipelines for vehicle telemetry, heartbeats, OTA campaign status, and ECU state changes.
• Build high-throughput data services and workers using Rust for payload routing, processing, and verification.
• Use Apache Kafka and AWS IoT Core for real-time data ingestion and event streaming.
• Leverage AWS MemoryDB for Redis for low-latency fleet state, campaign progression, and session management.
• Build resilient pipelines capable of handling intermittent connectivity, noisy networks, and out-of-order data.

Monitoring & Analytics  

• Build real-time dashboards for fleet health, firmware versions, OTA campaigns, and update progress.
• Define and monitor key OTA metrics including success/failure rates, retry rates, failure categories, and completion time.
• Implement automated alerting and anomaly detection for unexpected failure spikes during staged or canary rollouts.
• Analyze logs, traces, and telemetry data to identify campaign bottlenecks, telemetry loss, and hardware-related failures.

Required Skills  

Mandatory  

• 4–6 years of experience in Data Engineering, Software Engineering, or IoT Backend Engineering.
• Strong hands-on experience with Rust for backend/data processing applications.
• Experience with AWS, particularly IoT Core, S3, ECS/EKS, and Lambda.
• Strong experience with Apache Kafka and real-time data pipelines.
• Hands-on experience with AWS MemoryDB for Redis or Redis Enterprise.
• Working knowledge of Python and SQL.
• Experience with MQTT, WebSockets, and HTTP/S protocols.
• Strong understanding of distributed systems, streaming data, and resilient data pipelines.

Preferred  

• Experience with firmware lifecycle management and OTA systems.
• Exposure to connected vehicles, automotive IoT, telemetry platforms, or connected hardware fleets.
• Experience with device shadows and fleet/device state management.
• Experience building telemetry dashboards using Power BI, Apache Superset, or custom dashboards.
• Experience with staged/canary deployments and automated failure recovery.

Primary Technology Stack  

• Languages: Rust, Python, SQL
• Cloud: AWS, IoT Core, S3, ECS/EKS, Lambda
• Streaming: Apache Kafka
• Caching & State: AWS MemoryDB for Redis, Redis
• IoT Protocols: MQTT, WebSockets, HTTP/S
• Analytics & Visualization: Power BI, Apache Superset
• Domain: Automotive IoT, Vehicle Telemetry, OTA, Firmware Management

Strong Databricks Architect Profile with end-to-end Lakehouse ownership

2

Mandatory (Experience 1) – Must have 10+ years of software engineering experience with atleast 5+ years in Data Engineering with hands on exposure to Databricks and strong ownership of end-to-end data pipeline development.

3

Mandatory (Experience 2) – Must have atleast 5+ years of expertise across the Databricks ecosystem — Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, Workflows, Unity Catalog

4

Mandatory (Tech skill 1) – Must have worked at architecture level, owning end-to-end design through deployment

5

Mandatory (Tech skill 2) – Must have strong experience with Python and SQL for data processing and Apache Spark for performance tuning & scalability

6

Mandatory (Tech skill 3) – Must have experience in large-scale data warehousing & advanced data modeling (3NF and dimensional) across batch and real-time systems

7

Mandatory (AI Exposure) – Must have at least a basic working understanding of how AI services or tools work

8

Mandatory (Communication) – Must have strong stakeholder management & requirement-gathering experience with US or UK clients

9

Mandatory (Company) – Must come from a B2B IT services or IT consulting background

10

Mandatory (Note) – CTC is inclusive of 5% variable

11

Preferred (Tech skill 1) – Azure Databricks or Azure data services experience (project runs on Azure DevOps)

12

Preferred (Tech skill 2) – MLflow or MLOps practices and AI use cases (RAG, AI/BI)

13

Preferred (Tech skill 3) – CI/CD, Databricks Asset Bundles (DABs) or equivalent packaging, Terraform or IaC, reusable deployment templates

14

Preferred (Integrations) – ServiceNow or enterprise system integrations

15

Preferred (Certifications) – Databricks (Data Engineer Associate or Professional, ML or GenAI tracks), Azure or AWS cloud certifications

Job Description:

Position: CAD/CAM Developer / CAD Software Developer

Experience: 3–6 years

Employment Type: Full-time

Location: Hybrid/ Remote

Job Summary

We are looking for a skilled CAD/CAM Developer to design, develop, customize, and optimize CAD-related software applications and plugins. The ideal candidate should have strong programming experience in C++, C#, and/or Python, along with hands-on experience in CAD APIs, 2D/3D geometry, computational geometry, mathematical modeling, and algorithm development.

The candidate will work closely with engineering and product teams to develop high-performance CAD solutions, automate design workflows, process 3D geometry and point-cloud data, and improve the accuracy and efficiency of engineering applications.

Key Responsibilities

• Develop and maintain CAD/CAM software applications, plugins, and automation tools.
• Develop solutions using C++, C#, Python OR .NET.
• Work with CAD APIs such as AutoCAD API, Revit API, or equivalent CAD SDKs.
• Develop algorithms for 2D/3D geometry processing and geometric modeling.
• Design and optimize computational geometry algorithms for complex engineering problems.
• Work with 3D models, point-cloud data, mesh data, and spatial information.
• Implement geometric operations including alignment, rotation, transformation, measurement, and shape/geometry extraction.
• Develop tools for CAD model validation, quality checking, and automated workflows.
• Optimize algorithms for performance, accuracy, and scalability.
• Integrate software components and third-party SDKs into CAD applications.
• Participate in code reviews, debugging, testing, and technical documentation.
• Collaborate with cross-functional teams including engineering, product, and technical teams.
• Follow Agile development practices and maintain source code using Git/SVN.

Required Skills

Programming

• C++
• C#
• Python
• .NET Framework / .NET Core
• Object-Oriented Programming
• Data Structures & Algorithms

CAD / Geometry

• CAD/CAM Software Development
• AutoCAD / Revit / Autodesk platforms
• CAD API / SDK development
• 2D/3D Geometry
• Computational Geometry
• Geometric Modeling
• Spatial Computing
• Mathematical Modeling
• Algorithm Development & Optimization

3D / Point Cloud – Preferred

• Point Cloud Processing
• 3D Reconstruction
• Mesh Processing
• Voxelization
• PCL / Open3D
• LAS / LAZ / E57 / PLY formats
• Coordinate Transformation

We are looking for an experienced Application Developer to design, develop, enhance, and maintain cloud-native applications on AWS. The ideal candidate should have strong experience in modern frontend development using Next.js/Express.js and TypeScript, backend development using Python, and serverless application development on AWS.

The role involves:

• Developing and maintaining frontend applications using Next.js, React, and TypeScript.
• Developing backend services using Python and serverless AWS technologies.
• Designing and implementing AWS Lambda functions.
• Developing workflows using AWS Step Functions.
• Designing and maintaining Amazon AppSync GraphQL schemas and resolvers.
• Implementing multi-tenancy across application services.
• Building reusable, scalable, and responsive frontend components.
• Integrating frontend applications with backend APIs and cloud services.
• Participating in architecture discussions and technical design reviews.
• Debugging production issues and optimizing performance.
• Collaborating with architects, DevOps, data engineering, QA, and business teams.
• Following coding standards, cloud-native best practices, and contributing to documentation and code reviews.

Must Have Skills:

Frontend Development

• Strong JavaScript / TypeScript experience
• Hands-on experience with Next.js / Express.js
• Strong React.js proficiency
• Experience with Redux (or equivalent state management libraries)
• Good knowledge of HTML5, CSS3, and Material UI
• Experience building reusable and responsive frontend components

Backend Development

• Strong Python development experience
• Experience with Python frameworks:
• FastAPI
• Flask
• Experience building RESTful APIs and backend services

AWS & Cloud Development:

Hands-on experience with serverless AWS services including:

• AWS Lambda
• AWS DynamoDB
• AWS Step Functions
• Amazon API Gateway
• Amazon AppSync
• Amazon SQS
• Amazon SNS
• Amazon S3
• Amazon Aurora PostgreSQL
• AWS Glue (Python Shell)
• Amazon Cognito
• Amazon CloudFront

Additionally:

• Experience deploying and maintaining cloud-native applications on AWS

Collaboration

Ability to work effectively with:

• Solution Architects
• DevOps Engineers
• Data Engineers
• QA Teams
• Product Owners
• Clients and Business Stakeholders

Other Qualifications

• Experience with AWS CDK
• Exposure to microservices architecture
• Knowledge of caching, queuing, and application performance optimization
• Exposure to AWS Well-Architected Framework and application security best practices
• Experience working on data-intensive applications
• Experience in effort estimation, documentation, and sprint planning
• Experience building highly scalable and high-performance cloud applications.

Key Responsibilities

• Implement enhancements and features for business users to support audit data corrections through the web application.
• Develop new features across web applications and internal systems, including frontend enhancements, forms, and dynamic content.
• Manage databases to ensure data integrity and validation.
• Maintain database schemas and data linkages across systems.
• Perform unit testing of implemented solutions.
• Execute UI enhancements and navigation updates.
• Maintain existing code, contribute to documentation, and collaborate with cross-functional teams. 

Location: Jaipur, Rajasthan (Work From Office)

Experience: 4+ Years

Job Type: Full-Time

We're looking for an AI Assisted Developer who is passionate about building modern applications using AI-powered coding tools. You'll leverage AI to accelerate development while delivering scalable, high-quality software solutions.

Key Responsibilities

• Build scalable web applications, APIs, and automation workflows.
• Leverage GitHub Copilot, Cursor, Claude Code, ChatGPT, and similar AI tools to improve development productivity.
• Optimize AI prompts and workflows for efficient coding.
• Apply best practices in system design, TDD, debugging, testing, and code reviews.
• Collaborate with Product, QA, and DevOps teams to deliver high-quality software.
• Stay up to date with emerging AI development tools and technologies.

Requirements

• 4+ years of software development experience.
• Proficiency in Python, JavaScript/TypeScript, or Go.
• Experience with React, Node.js, or modern development frameworks.
• Hands-on experience with GitHub Copilot, Cursor, Claude Code, ChatGPT, or similar AI coding tools.
• Strong understanding of Git, CI/CD, SQL/NoSQL, system design, and software engineering principles.
• Excellent problem-solving and communication skills.

Preferred: Experience with LangChain, LangGraph, OpenAI APIs, FastAPI, Agentic AI, MCP, Prompt Engineering, AI Automation, or AWS/Azure/GCP.

Apply Now

Application Form: https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort

Location: Jaipur (Work From Office)

Employment Type: Full-Time

We're looking for a GenAI Engineer (LLM Engineer) to build scalable AI-powered SaaS applications using Large Language Models (LLMs). You'll develop intelligent AI workflows, integrate LLMs into production systems, and build secure, high-performance AI solutions.

Key Responsibilities

• Integrate LLM APIs (OpenAI, Claude, Hugging Face) into production applications.
• Design and optimize RAG pipelines and prompt engineering workflows.
• Build and manage Vector Databases (Pinecone, Weaviate, pgvector).
• Optimize AI performance, latency, and operational cost.
• Ensure secure, scalable AI architecture.
• Collaborate with Product and Engineering teams to deliver AI-powered features.

Requirements

• 3+ years of backend development using Python, Go, or Node.js.
• Hands-on experience with LLMs, LangChain or LlamaIndex.
• Strong understanding of RAG, Prompt Engineering, and Vector Databases.
• Experience with AWS, GCP, or Azure.
• Knowledge of APIs, Microservices, and AI application development.

Preferred: Experience in SaaS/FinTech, LLMOps, or Model Fine-tuning.

Education: B.Tech, BCA, or equivalent technical qualification.

Apply Now

Application Form: https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort

Skills Referential (Required knowledge, skills and abilities)

Technical Skills:

Python

Pyspark

SQL

ETL Aws, Azure, gcp

Key Responsibilities  

• Design, build, and optimize scalable data pipelines for AI/ML applications.
• Develop, train, evaluate, and deploy Machine Learning and Deep Learning models.
• Build production-ready LLM applications using Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases.
• Fine-tune open-source and foundation models using domain-specific datasets.
• Develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, and lifecycle management.
• Perform data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation.
• Develop APIs and AI services for production deployment.
• Collaborate with cross-functional teams to deliver scalable AI-driven solutions.
• Monitor model performance, troubleshoot production issues, and maintain technical documentation.

Required Skills  

Mandatory  

• 1–3 years of experience in Data Science, Data Engineering, or AI/ML development.
• Strong programming skills in Python and SQL.
• Hands-on experience with Machine Learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience building LLM-powered applications using RAG, Prompt Engineering, and Embeddings.
• Hands-on experience with LangChain, LlamaIndex, CrewAI, or n8n for LLM orchestration and AI workflow automation.
• Experience in LLM fine-tuning and working with Hugging Face models.
• Knowledge of MLOps concepts including model deployment, monitoring, versioning, and CI/CD.
• Experience with Git, REST APIs, Linux environments, and data processing libraries.

Preferred  

• Experience with vector databases such as Pinecone, Chroma, Milvus, or Weaviate.
• Familiarity with Docker, Kubernetes, and MLflow.
• Exposure to Apache Spark or Airflow for data engineering workflows.
• Experience with cloud platforms (AWS, Azure, or GCP).

Primary Technology Stack  

• Languages & Data Processing: Python, SQL, Pandas, NumPy, Apache Spark
• AI & Machine Learning: PyTorch, TensorFlow, Scikit-learn
• Application Frameworks: LangChain, LlamaIndex, CrewAI, n8n
• Core Methodologies: Retrieval-Augmented Generation (RAG), Model Fine-Tuning, Prompt Engineering, Embeddings
• Models & Infrastructure: OpenAI APIs, Hugging Face Ecosystem, Embedding Models
• Vector Databases: Pinecone, Chroma, Milvus, Weaviate
• Databases: PostgreSQL, MongoDB
• MLOps & DevOps: Docker, Kubernetes, MLflow, CI/CD, Git
• Cloud Platforms: AWS, Azure, GCP

Experience: 1–3 Years

Domain: Data Science | Data Engineering | Machine Learning | Generative AI | MLOps

What You Bring • Bachelor’s degree in computer science, Software Engineering, or related field with 7+ years of relevant professional experience. • Deep production experience with Python and JavaScript/TypeScript across backend and frontend, with demonstrated ability to work comfortably across the full stack. • Strong experience with modern frontend frameworks (such as Next.js or React) and backend API development. • Extensive experience with cloud platforms (AWS preferred; Azure or GCP also valued), including infrastructure-as-code tools (such as CloudFormation or Terraform). • Deep Working knowledge of multiple database paradigms, including relational databases (such as PostgreSQL), document databases, and key-value stores (such as Redis), with the ability to select the right storage technology for each problem. • Strong experience with CI/CD pipelines (such as GitHub Actions), containerisation, and production deployment strategies. • Demonstrable fluency with AI coding tools (such as Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on AI-augmented development practices. • Hands-on experience architecting production generative AI applications (LLM integrations, vector databases, RAG systems, evaluation pipelines) is essential. • Experience leading technical initiatives across multiple teams, mentoring engineers, and establishing engineering practices is required. • Experience navigating ambiguous problem spaces, working directly with business stakeholders and end users, and shipping working solutions rapidly is required. • Experience in an embedded, forward-deployed, or consulting-style engineering model is a strong plus. • Must have exceptional communication skills and demonstrated ability to influence at senior levels. This role requires comfort leading across ambiguous environments, building trust-based relationships with commercial stakeholders at all levels, developing junior and mid-level engineers, and making strategic decisions that balance delivery speed with architectural integrity. You will shape engineering practices across your area and be expected to lead multi-team initiatives.  

We want a highly experienced engineer with expertise as follows:

● React Native: very high level of proficiency; this should be a core strength

● JavaScript / TypeScript: very high level of proficiency

● React: high proficiency, with strong experience building customer-facing web

applications

● Mobile application development: very strong understanding of app architecture,

performance, debugging, reliability, and release quality

● Python / backend systems: medium to high proficiency; comfortable contributing to

APIs and backend workflows

● Performance optimization: strong experience improving responsiveness and efficiency

across application and processing layers

● Database design and caching: solid experience designing efficient data access

patterns and improving performance of critical operations

● AWS / S3 / async pipelines: working experience, especially in systems involving

uploads, processing, and media workflows

● Developer tools and local development workflows: strong experience improving

engineering productivity and reducing friction in how teams build, test, and ship

● Swift / native iOS development: nice to have, but not required

● Product thinking / customer empathy: strong ability to understand user needs, work

through ambiguity, and help shape product direction

The ideal candidate has strong experience building polished, production-quality applications in

React Native and React, and is comfortable contributing across backend systems where

needed. This person should be excited to understand customer workflows closely and help

shape product direction, not just execute tickets.

What you’ll do

You will work on high-impact product and platform problems, including:

● Building and improving the core React Native application used by customers in the field

● Developing mobile product experiences that help customers capture, review, and act on

ergonomics risk insights

● Building frontend UI for critical new features in the web application using React

● Improving app performance, responsiveness, reliability, and release quality across

mobile and web

● Improving the speed and reliability of video ingestion and re-encoding into web-playable

formats

● Implementing intelligent caching and data access patterns to speed up critical database

operations

● Improving developer tools and local development workflows across mobile, web, and

backend systems

● Contributing to backend services and APIs that power our mobile and web experiences

● Supporting native iOS integrations where needed

● Working closely with product, customers, and the broader engineering team to turn

real-world operational pain points into shipped product improvements

Responsibilities

● Own major product features end-to-end, from product thinking through implementation

and release

● Build high-quality, performant mobile experiences using React Native

● Build intuitive, reliable web experiences using React

● Contribute to backend services and APIs in Python that support product workflows

● Improve app quality through better testing, debugging, observability, and engineering

workflows

● Identify and resolve bottlenecks in video, processing, storage, and database systems

that affect product performance

● Help define engineering best practices for application quality, release processes, and

developer productivity

● Collaborate cross-functionally with product and customer-facing teams to prioritize the

right problems

● Raise the technical bar through strong code reviews, debugging discipline, and

pragmatic architectural decisions

Must-have qualifications

●8-14 years of professional software engineering experience

● Strong hands-on expertise in React Native

● Strong hands-on expertise in JavaScript/TypeScript

● Strong experience with React

● Experience building and shipping production-quality mobile applications

● Strong understanding of mobile architecture, app lifecycle, performance, and debugging

● Experience building customer-facing web applications

● Experience working with backend APIs and full-stack product development

● Experience improving developer productivity through tools, local development setups,

testing workflows, or internal engineering systems

● Strong product sense and ability to translate ambiguous customer needs into scoped

technical solutions

● Excellent communication skills and a high degree of ownership

Experience Required: Minimum 8 Years

About the Role:

Key Responsibilities

• Design and manage organization-wide MIS reports, dashboards, and executive reports.
• Develop automated reporting solutions using Python, VBA Macros, Power Query, and Advanced Excel.
• Analyze large datasets and provide business insights to leadership.

Eligibility Criteria

• 5+ years of experience in Business Intelligence, MIS, Business Analytics, or Data Analytics.
• Strong analytical and logical thinking with the ability to understand business requirements and convert data into meaningful business insights.
• Experience in developing dashboards and management reports using any Business Intelligence tool (Power BI, Tableau, Zoho Analytics, etc.).

Apply Now:

https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort

Hiring for Prinipal / Lead Data Architect

Exp : 12 - 16 yrs

Work Location : Bengaluru

Shift Timings : UK

Mode of Interview : F2F

Skills :

Databricks, Python, Scala, SQL, Snowflake, Structured Streaming, Apache Kafka, Flink/AWS.

10+ years of progressive experience in Data Engineering, Data Warehousing, and Data Architecture.

Hiring for Python Full Stack Lead

Exp : 6 - 10 yrs

Edu : BE/B.Tech 60 - 65 %

Work Location Pune WFO

Skills : 4+ years of experience in Python

2+ years of experience in React Js

Rest Framework

Lead Exp must

Observability Engineer (AppDynamics)

Hyderabad

Exp: 8+years of exp

Mandate Skills: AppDynamics, Splunk, Python (Scripting knowledge)

Primary Skill Set:

• AppDynamics administration
• SPLOC administration
• Enterprise monitoring and observability
• Application performance monitoring
• Alerting and event management
• Monitoring strategy and design
• Platform configuration and governance
• Python scripting
• Monitoring automation

Secondary Skills:

• Glassbox monitoring
• Customer journey observability
• GenAI concepts for operations       
• Log, metric, and trace telemetry
• Dashboarding and visualization

Job Title: AI Architecture Intern

Company: PGAGI Consultancy Pvt. Ltd.

Location: Remote

Employment Type: Internship

Position Overview

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

Duration: 6 months

Key Responsibilities:

• AI System Architecture Design: Collaborate with the technical team to design robust, scalable, and high-performance AI system architectures aligned with client requirements.
• Client-Focused Solutions: Analyze and interpret client needs to ensure architectural solutions meet expectations while introducing innovation and efficiency.
• Methodology Development: Assist in the formulation and implementation of best practices, methodologies, and frameworks for sustainable AI system development.
• Technology Stack Selection: Support the evaluation and selection of appropriate tools, technologies, and frameworks tailored to project objectives and future scalability.
• Team Collaboration & Learning: Work alongside experienced AI professionals, contributing to projects while enhancing your knowledge through hands-on involvement.

Requirements:

• Strong understanding of AI concepts, machine learning algorithms, and data structures.
• Familiarity with AI development frameworks (e.g., TensorFlow, PyTorch, Keras).
• Proficiency in programming languages such as Python, Java, or C++.
• Demonstrated interest in system architecture, design thinking, and scalable solutions.
• Up-to-date knowledge of AI trends, tools, and technologies.
• Ability to work independently and collaboratively in a remote team environment

Perks:

- Hands-on experience with real AI projects.

- Mentoring from industry experts.

- A collaborative, innovative and flexible work environment

Compensation:

- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.

After completion of the internship period, there is a chance to get a full-time opportunity as an AI/ML engineer.

Preferred Experience:

• Prior experience in roles such as AI Solution Architect, ML Architect, Data Science Architect, or AI/ML intern.
• Exposure to AI-driven startups or fast-paced technology environments.
• Proven ability to operate in dynamic roles requiring agility, adaptability, and initiative.

Location: Pune/Bengaluru

As a Senior Software Engineer, you will tackle a highly challenging role within our Cyber Security Engineering integration development team. You will be responsible for the End-to-End (E2E) delivery of projects from gathering customer requirements to deploying high-performance data exchange solutions on-prem or in the cloud. We are looking for a Systems-Level Thinker who can seamlessly transition between building complex integrations and architecting high-throughput, low-latency backends. Because each integration may require a different technical approach, we value engineers who love reskilling, following agile best practices, and maintaining an evolving mindset.

Core Responsibilities

Technical Leadership and Architecture

● Systems Engineering: Design, build, and optimize high-throughput, low-latency backend systems and data-exchange layers.

● Architecture and Integration: Participate in planning, defining, and exploring solution alternatives. Architect and estimate deep technical custom solutions and integrations across diverse enterprise tech stacks. ● Stream Processing: Implement event-driven architectures, manage backpressure, and handle real-time state management across security platforms.

● Delivery Ownership: Own projects end-to-end, defining and implementing enablers to evolve solution intent directly alongside our Agile teams.

Team Leadership and Quality

● Mentorship: Actively lead, coach, and mentor junior developers, providing technical guidance to foster professional development.

● Engineering Excellence: Oversee code reviews, build robust CI/CD pipelines, enforce strict quality checks, and ensure rigorous adherence to coding standards.

● Agile Execution: Actively participate in Agile development, including writing, breaking down, and estimating User Stories.

Customer and Stakeholder Collaboration

● Customer Delight: Maintain a strong customer-first attitude while designing, building, and deploying products.

● Technical Communication: Articulate complex technical trade-offs clearly to both business stakeholders and engineering teams.

● Pipeline Management: Manage customer relationships effectively to ensure a continuous flow of project scope, maintaining clear team backlogs.

Job Requirements

● Experience: 5+ years of proven software engineering experience, with a track record of leading small engineering teams or mentoring junior devs.

● High-Throughput Backend Focus: 5+ years of experience engineering robust, real-time backends specifically using Go (Golang) or Java.

● Polyglot and Integration Capability: Deep expertise in at least one or two additional languages/frameworks from our ecosystem: Python, TypeScript, Node.js, React.js, Angular, C#, or C++.

● Computer Science Fundamentals: Excellent knowledge of complex Data Structures, algorithms, and their correct situational usage.

● Adaptability: A passionate programmer who is genuinely open and excited to learn new software development skills as required by changing project demands.

Bonus / Added Advantages

● AI & Intelligent Automation: Hands-on knowledge of AI concepts, Large Language Models (LLMs), and experience building or integrating AI agents to automate complex workflows or security processes.

● Cybersecurity Domain: Experience in the cybersecurity space (SIEM, SOAR, or platform security).

● Modern Web Tech: Strong experience in developing software using modern web technologies.

● E2E Lifecycle: Proven background handling a project completely from discovery to cloud/on-prem deployment.

● Open Source: Active contributions to the Open Source community. (Please share your GitHub/GitLab links in your application!)

About the Role

We are looking for a hands-on Principal Engineer who owns enterprise integration architecture from end to end — from the first whiteboard sketch through production delivery and ongoing governance. This is not a management role, and it is not a specialist role. We are not looking for an Angular architect, a Java architect with cloud exposure. We need a true Full Stack Integration Architect who has designed, built, and governed how large-scale enterprise systems connect, communicate, and operate reliably at scale.

You will be expected to go deep on integration design, backend engineering, data architecture, cloud infrastructure, and front-end development — and to defend every decision under rigorous technical scrutiny. If your experience is anchored in one layer or one language, this is not the right opportunity.

What You Will Own

• End-to-end integration architecture across cloud platforms (AWS, Azure, GCP), on-premises systems, and third-party services — designed, delivered, and governed by you
• Definition and enforcement of integration patterns across the enterprise: API-first, microservices, event-driven, and real-time and batch processing
• Seamless data flow, application interoperability, and fault tolerance across mission-critical platforms
• Quality and testing strategy across integrated solutions — automation frameworks, release readiness, validation, and quality governance
• Full-stack engineering across all layers: front-end, backend services, data, and cloud infrastructure
• GenAI and LLM integration into production-grade digital platforms
• Technical mentorship across engineering levels and cross-team architectural influence
• Clear communication of complex architectural decisions to both engineering teams and business stakeholders

What You Must Have

• 15+ years of hands-on software engineering experience with a strong track record in enterprise-scale distributed systems
• Proven end-to-end integration architecture experience — you have designed, governed, and delivered enterprise integrations across complex, heterogeneous environments; not just implemented someone else's design
• Genuine full-stack depth across all layers:
• Front-end: Angular, TypeScript
• Backend: Java, Python, Go, or Node.js — at least one deeply, others functionally
• Data: SQL, NoSQL, caching (Redis), event streaming platforms
• Strong database knowledge in both theory and practice — relational, NoSQL, distributed data, and streaming
• Cloud-native hands-on experience across at least one of AWS, Azure, or GCP — Kubernetes, Docker, and Infrastructure as Code (Terraform) are expected
• CI/CD pipeline experience tied to enterprise release cycles and quality governance
• The ability to clearly articulate the technical design, tradeoffs, and problem-solving approach behind your own recent work — this will be probed in depth during interviews

Integration & API Technologies

You should have hands-on experience across several of the following:

REST · GraphQL (Apollo Federation or similar) · gRPC · Kafka or equivalent event streaming · Microservices architecture · Event-driven architecture · B2B and internal system integrations · Real-time and batch integration patterns

What Will Strengthen Your Profile

• GCP-native database experience: BigQuery, Spanner, Bigtable
• Production-grade GenAI or LLM integration — not just prototypes or proof of concepts
• Experience with AI development tools: Cursor, GitHub Copilot, Vertex AI Studio, Claude Code
• Healthcare or regulated-industry platform experience
• MLOps or AI lifecycle management
• Identity, security, and privacy architecture at enterprise scale
• Observability tooling: Datadog, Prometheus, Grafana

Do Not Apply If

• You are primarily an Angular Architect, a Java architect, or strong in one layer only — this role demands genuine end-to-end depth across the full stack
• You cannot walk through the architecture, implementation decisions, and tradeoffs of your own recent projects with technical precision
• You have not designed or governed integrations at enterprise scale across distributed, heterogeneous systems
• Your backend, database, or integration experience is surface-level, theoretical, or limited to a single technology

Why This Role

This role carries real architectural authority at a large enterprise. You will set integration direction across business-critical platforms, influence engineering standards, and solve problems that matter at significant scale. The technical bar is deliberately high — because the impact is real.

Job Summary

We are looking for an experienced Senior Python Full Stack Developer with 5+ years of hands-on experience in Python, Django, Flask, and React.js. The ideal candidate should have strong expertise in developing scalable web applications, building RESTful APIs, and working across both backend and frontend technologies.

The candidate will be responsible for designing, developing, testing, and maintaining high-quality applications while collaborating closely with product, design, QA, and other engineering teams.

Key Responsibilities

• Design, develop, and maintain scalable web applications using Python, Django, and Flask.
• Develop responsive and user-friendly frontend applications using React.js.
• Build and integrate RESTful APIs and third-party services.
• Design efficient database structures and write optimized queries.
• Work with databases such as PostgreSQL, MySQL, or MongoDB.
• Write clean, reusable, maintainable, and well-documented code.
• Perform code reviews and ensure adherence to development best practices.
• Identify and resolve application performance and production issues.
• Collaborate with cross-functional teams to understand requirements and deliver solutions.
• Participate in architecture and technical design discussions.
• Develop unit and integration tests to ensure application reliability.
• Troubleshoot, debug, and optimize existing applications.
• Follow Agile/Scrum development practices and contribute to sprint planning and estimation.

Required Skills

• 5+ years of professional experience in software development.
• Strong proficiency in Python.
• Hands-on experience with Django and Flask.
• Strong experience with React.js and modern frontend development.
• Good understanding of HTML, CSS, JavaScript, and TypeScript.
• Strong experience in developing and consuming REST APIs.
• Good knowledge of SQL and relational databases.
• Experience with Git/GitHub/GitLab.
• Strong understanding of object-oriented programming and software design principles.
• Experience with debugging, performance optimization, and application security.
• Good understanding of Agile/Scrum methodologies.

Good to Have

• Experience with AWS, Azure, or GCP.
• Knowledge of Docker and Kubernetes.
• Experience with CI/CD pipelines.
• Familiarity with Redis, Celery, or message queues.
• Experience working with microservices architecture.
• Knowledge of automated testing frameworks such as PyTest.
• Experience working in cloud-based production environments.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Ability to work independently and take ownership of assigned tasks.
• Ability to mentor junior developers and contribute to technical decisions.
• Strong attention to quality and detail.

Job Summary

We are seeking a skilled Azure Data Engineer with hands-on experience in Azure Data Services, Azure Databricks, Python, PySpark, and SQL. The ideal candidate will be responsible for designing, developing, and optimizing scalable data pipelines and data processing solutions to support business intelligence, analytics, and reporting requirements.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks and PySpark.
• Build and optimize data processing workflows using Python and SQL.
• Develop and manage data ingestion pipelines from multiple structured and unstructured data sources.
• Work with Azure Data Factory (ADF) to orchestrate and schedule data pipelines.
• Implement data transformation and cleansing logic using PySpark.
• Optimize SQL queries and Spark jobs for performance and scalability.
• Collaborate with data architects, analysts, and business stakeholders to understand data requirements.
• Ensure data quality, integrity, and governance across the data platform.
• Monitor, troubleshoot, and resolve production data pipeline issues.
• Follow coding standards, version control, and CI/CD best practices.

Required Skills

• Strong experience with Microsoft Azure cloud services.
• Hands-on experience with Azure Databricks.
• Strong programming skills in Python.
• Expertise in PySpark for large-scale data processing.
• Strong SQL skills, including query optimization and performance tuning.
• Experience with Azure Data Factory (ADF).
• Knowledge of Delta Lake, Spark SQL, and Databricks notebooks.
• Experience with Git or Azure DevOps for source code management.
• Understanding of data warehousing concepts and ETL/ELT processes.

Preferred Skills

• Experience with Azure Synapse Analytics.
• Knowledge of Delta Live Tables (DLT).
• Experience with Azure Data Lake Storage (ADLS Gen2).
• Familiarity with Unity Catalog and data governance.
• Exposure to CI/CD pipelines and infrastructure-as-code.
• Experience working in Agile/Scrum environments.

Job Summary:

We are seeking a highly skilled Capability Lead in Software Testing to join our dynamic team. The ideal candidate will be responsible for leading testing initiatives, ensuring quality assurance processes are effectively implemented, and driving continuous improvement in testing methodologies. This role requires a strong foundation in Python, as well as a deep understanding of software testing principles and practices.

Responsibilities:

• Lead and manage software testing projects, ensuring adherence to quality standards and timelines.
• Develop and implement comprehensive testing strategies, including automated and manual testing processes.
• Collaborate with cross-functional teams to define testing requirements and ensure alignment with project goals.
• Utilize Python to create and maintain automated test scripts, enhancing testing efficiency and coverage.
• Analyze test results, identify defects, and work with development teams to resolve issues promptly.
• Provide mentorship and guidance to junior testing team members, fostering a culture of quality and continuous learning.
• Stay updated with industry trends and best practices in software testing and quality assurance.
• Prepare detailed test documentation, including test plans, test cases, and test reports.
• Participate in project planning and status meetings, providing insights on testing progress and challenges.

Mandatory Skills:

• Proficiency in Python programming for test automation.
• Strong understanding of software testing methodologies, including functional, regression, and performance testing.
• Experience with test management tools and defect tracking systems.
• Excellent analytical and problem-solving skills.
• Strong communication skills, both verbal and written, with the ability to articulate complex technical concepts to non-technical stakeholders.

Preferred Skills:

• Familiarity with Agile and DevOps methodologies.
• Experience with continuous integration and continuous deployment (CI/CD) practices.
• Knowledge of other programming languages and testing frameworks.
• Experience in performance testing tools and techniques.
• Understanding of cloud-based testing environments.

Qualifications:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Relevant certifications in software testing (e.g., ISTQB, CSTE) are a plus.
• Demonstrated ability to lead testing initiatives and drive quality improvements.
•  

The Role:

We are seeking a highly skilled Sr Embedded Software Engineer (Python & C++) to manage and improve the software development lifecycle for device firmware systems. The primary focus of this role is to ensure firmware operational reliability, fail-safe implementation, certification compliance, and robust production deployment.

This role is ideal for an engineer experienced in system-level software, firmware validation, testing automation, and production readiness — but not focused on low-level hardware design.

Experience: 6-10 years

Job Location: Hyderabad

Job Type: Permanent

CORE FOCUS AREAS

• Ensure firmware operates reliably in production environments

• Implement and validate fail-safe mechanisms and fallback logic

• Maintain certification compliance across firmware releases

• Drive robust, repeatable production deployment pipelines

• Support field debugging and OTA update validation

IDEAL CANDIDATE PROFILE

• Strong hands-on experience in Python and C++ development

• Background in system-level software and firmware validation

• Experience with testing automation and production readiness

• Comfortable working closely with embedded engineers

• Not required to have low-level hardware design expertise

KEY RESPONSIBILITIES

FIRMWARE OPERATIONAL STABILITY

• Ensure firmware operates reliably in production environments

• Implement and validate fail-safe mechanisms and fallback logic

• Monitor watchdog systems, timeout handling & safe state transitions

• Work closely with embedded engineers to validate firmware behavior

PYTHON & C++ DEVELOPMENT

• Develop firmware communication layers & device control applications

• Build diagnostic tools and test automation frameworks

• Optimize performance and memory handling in C++ applications

• Develop production-ready Python tools for deployment, logging & validation

FAIL-SAFE & SAFETY IMPLEMENTATION

• Implement safe boot validation, error recovery & redundancy logic

• Build communication retry systems & safe shutdown protocols

• Design state machines for controlled device operation

• Ensure safe-state transitions on power, comms or hardware failure

PRODUCTION DEPLOYMENT & VALIDATION

• Create secure and repeatable firmware deployment pipelines

• Implement boot image validation, signature verification & rollback

• Develop health monitoring and diagnostic utilities & CI/CD Pipelines

• Support field debugging and OTA update validation

Linux Environment

• Work in Linux-based environments for firmware development, debugging, and deployment — including shell scripting, process/service management, and system diagnostics.

• Own unit testing, integration testing & production release management

• Ensure code quality and compliance with internal standards

IoT + AI

Building the tech behind India's Reverse Vending Machines

SUCCESS METRICS

• Firmware reliability — stable, uninterrupted operation in production environments

• Fail-safe coverage — validated fallback logic, redundancy & safe-state transitions

• Linux Environment - Use Linux for development till deployment

• Deployment success rate — secure, repeatable pipelines with clean rollbacks

• Code & release quality — test coverage, code review discipline & CI/CD health

• Field performance — OTA update success and turnaround on field debugging