488 Python Jobs in Mumbai | Python Job openings in Mumbai

Job Description:

We are looking for an experienced Python Full Stack Developer with strong expertise in Python, Django, React.js, HTML, JavaScript, and RESTful APIs. The ideal candidate should have experience developing scalable web applications, building backend services, and integrating frontend components with backend APIs.

Key Responsibilities:

• Develop and maintain web applications using Python and Django.
• Build responsive user interfaces using React.js, HTML, and JavaScript.
• Design, develop, and integrate RESTful APIs.
• Collaborate with cross-functional teams to deliver high-quality solutions.
• Troubleshoot issues and optimize application performance.
• Python
• HTML
• JavaScript
• React.js
• Django
• RESTful APIs

We are seeking a highly skilled Full-stack Developer to join our dynamic 

team as a Delivery Module Lead. The ideal candidate will possess strong expertise in Python 

and front-end technologies, enabling them to design, develop, and maintain robust web 

applications. This role requires a proactive individual who can collaborate effectively with 

cross-functional teams to deliver high-quality software solutions that meet business needs. 

Responsibilities: 

∙Design, develop, and maintain scalable web applications using Python and front-end 

technologies. 

∙Collaborate with product managers, designers, and other developers to define project 

requirements and deliver solutions that meet user needs. 

∙Implement responsive user interfaces and ensure optimal performance across various 

devices and browsers. 

∙Write clean, maintainable, and efficient code while adhering to best practices and 

coding standards. 

∙Conduct code reviews and provide constructive feedback to team members to enhance 

code quality. 

∙Debug and troubleshoot issues in existing applications, providing timely resolutions. 

∙Stay updated with emerging technologies and industry trends to continuously improve 

development processes. 

∙Participate in Agile development processes, including sprint planning, daily stand-

ups, and retrospectives. 

Mandatory Skills: 

∙Proficient in Python programming language. 

∙Strong knowledge of front-end technologies such as HTML, CSS, and JavaScript. 

∙Experience with front-end frameworks like React, Angular, or Vue.js. 

∙Familiarity with back-end frameworks such as Django or Flask. 

∙Understanding of RESTful APIs and web services. 

∙Experience with version control systems, preferably Git. 

∙Strong problem-solving skills and attention to detail. 

We are seeking a highly skilled Full-stack Developer to join our dynamic 

team as a Delivery Module Lead. The ideal candidate will possess strong expertise in Python 

and front-end technologies, enabling them to design, develop, and maintain robust web 

applications. This role requires a proactive individual who can collaborate effectively with 

cross-functional teams to deliver high-quality software solutions that meet business needs. 

Responsibilities: 

∙Design, develop, and maintain scalable web applications using Python and front-end 

technologies. 

∙Collaborate with product managers, designers, and other developers to define project 

requirements and deliver solutions that meet user needs. 

∙Implement responsive user interfaces and ensure optimal performance across various 

devices and browsers. 

∙Write clean, maintainable, and efficient code while adhering to best practices and 

coding standards. 

∙Conduct code reviews and provide constructive feedback to team members to enhance 

code quality. 

∙Debug and troubleshoot issues in existing applications, providing timely resolutions. 

∙Stay updated with emerging technologies and industry trends to continuously improve 

development processes. 

∙Participate in Agile development processes, including sprint planning, daily stand-

ups, and retrospectives. 

Mandatory Skills: 

∙Proficient in Python programming language. 

∙Strong knowledge of front-end technologies such as HTML, CSS, and JavaScript. 

∙Experience with front-end frameworks like React, Angular, or Vue.js. 

∙Familiarity with back-end frameworks such as Django or Flask. 

∙Understanding of RESTful APIs and web services. 

∙Experience with version control systems, preferably Git. 

∙Strong problem-solving skills and attention to detail. 

We are seeking talented software developers who are passionate about coding and building & scaling

products. If you love taking on new challenges and have a problem solving mindset to solve problems through

code, you will be a perfect fit for our rockstar engineering team.

Roles and Responsibilities:

● Design and develop backend architectures to support robust, scalable, and secure web applications and

systems with a focus on backend development using Django.

● Design, implement and maintain high quality RESTful APIs to support seamless communication between

frontend, backend and other services.

● Design, implement, and maintain database schemas. Ensure the integrity, performance, and security of

data.

● Ensure the scalability and reliability of our backend infrastructure on AWS. Ensure reliable management of

infrastructure on cloud aiming for 0 downtime of systems.

● Write clean, maintainable, and efficient code, while adhering to best practices and industry standards.

Develop and maintain documentation for our backend systems, APIs, and data models.

● Conduct high quality code reviews and provide feedback to other team members to ensure best practices

are adhered to.

● Take ownership of the development, testing, and deployment of web applications. Break down high-level

business problems into smaller chunks and build systems.

● Work closely with the frontend development team, product managers, and designers to plan new features

and optimize existing ones.

● Constantly aim to improve performance and optimize systems by identifying bottlenecks and resolving

them for increased efficiency.

● Stay up-to-date with the latest technologies such as LLMs, and implement them as and when required

Skills and Qualifications:

● Bachelor's degree in Computer Science, Computer Engineering or a related field.

● 4+ years of experience in full-stack web development, with a focus on backend development.

● Strong proficiency in Python and Django, including experience with Django Rest Framework.

● Experience working with SQL/PostgreSQL databases, including schema design, querying, and

optimization.

● Proficiency in AWS services such as EC2, RDS, S3, and Lambda.

● Familiarity of integrations with third party services and open source frameworks

● Strong understanding of data structures, algorithms, and software design patterns.

● Experience with containerization and orchestration technologies such as Docker and Kubernetes is a plus.

● Familiarity with LLM frameworks such as Langchain, OpenAI, Anthropic, LLaMa is a plus.

● Strong problem-solving skills and ability to work in a fast-paced environment.

● Excellent communication and collaboration skills.

Solid product experience and an educational background from Tier‑1 universities are preferred.

As a Senior AI Engineer, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities. 

In this role, you will: 

• Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance. 
• Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features. 
• Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability. 
• Work with SQL and NoSQL databases to implement efficient data models and service access patterns. 
• Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs). 
• Use AI powered engineering tools to improve development quality, speed, and productivity. 
• Mentor engineers, supporting them in technical planning, implementation, and best practices. 
• Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure. 
• Write unit and integration tests and participate in code reviews to uphold engineering excellence. 
• Investigate production issues, ensuring timely and effective solutions. 
• Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies. 

Who You’ll Work With 

You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction. 

What Makes You a Qualified Candidate 

(Nonnegotiable qualifications) 

• Bachelor’s degree in Computer Science or equivalent from a recognized institution. 
• 5+ years of experience in backend services, distributed systems, or data platform development. 
• Strong proficiency in Java, Go, or Python for service development. 
• Good understanding of design principles, distributed system patterns, and service framework. 
• Hands-on experience designing and developing RESTful APIs. 
• Experience with SQL and NoSQL databases and data modelling. 
• Strong debugging, problem solving, and troubleshooting skills. 
• Experience with modern containerization and orchestration tools such as Kubernetes. 
• Knowledge of public cloud platforms. 
• Experience with AI productivity tools (e.g., GitHub Copilot). 
• Ability to work independently, drive workstreams, and deliver high quality outcomes. 
• Strong communication and collaboration skills. 

What You’ll Bring 

(Preferred qualifications) 

• Familiarity with messaging systems such as Kafka. 
• Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs. 
• A track record of influencing design decisions and driving engineering best practices. 
• The ability to mentor engineers and guide them through design, planning, and execution. 
• A proactive mindset and comfort working in fast paced, dynamic environments. 
• Curiosity, adaptability, and a passion for building impactful AI-driven products. 

Job Title: Senior Fullstack Engineer – ServiceNow

Company: Cloud Sara Technologies Pvt. Ltd.

Experience: 8–12 Years

Location: Bangalore, Hyderabad, Chennai, Mumbai, Ahmedabad

Work Mode: Hybrid – 2 days work from office mandatory

Employment Type: Contract – 6 Months

Notice Period: Immediate Joiners Only

Shift: 1:00 PM – 11:00 PM IST

Interview Process: L1 in-person interview is mandatory

Job Description

We are looking for an experienced Senior Fullstack Engineer with strong hands-on ServiceNow development expertise, QA automation capabilities, and general full-stack development skills.

The candidate will handle ServiceNow integration defects, production troubleshooting, automated testing, release management, and internal application maintenance.

Key Responsibilities

• Handle L2 support tickets, escalations, and ServiceNow integration issues.
• Resolve L3 defects involving ServiceNow ITSM/CMDB, Flow Designer, Scripted REST APIs, Business Rules, GlideRecord, and server-side scripting.
• Perform root-cause analysis for production incidents and integration issues.
• Review code and contribute to full-stack development and maintenance.
• Develop and maintain automated tests using Python and Playwright.
• Validate APIs using Postman and data using SQL.
• Manage test cases in Qase and integrate automated tests into CI/CD pipelines.
• Maintain release documentation, Update Sets, XML exports, and release processes.
• Support customer technical escalations and distributed-system debugging.
• Use AI-assisted development and QA tools to improve productivity.

Mandatory Skills

• 6+ years of hands-on ServiceNow development experience.
• ServiceNow ITSM, CMDB, Flow Designer, Scripted REST APIs, Business Rules, GlideRecord, and server-side scripting.
• OAuth2-based integrations and troubleshooting across systems.
• Python and Playwright test automation.
• API testing using Postman and SQL validation.
• React, TypeScript, and API-driven backend development.
• GitHub, CI/CD, and ServiceNow deployment tools.
• Experience with AI-assisted QA tools such as Claude or Codex.

Preferred Skills

• ServiceNow CSA or CIS certifications.
• GitHub Actions and release management experience.
• Semantic versioning and changelog management.
• Customer-facing production support and on-call experience.

Important Conditions

• Immediate joiners only.
• Hybrid work with 2 days in office mandatory.
• Must be available for the 1 PM–11 PM IST shift.
• Must attend the L1 interview in person.
• Six-month contract engagement.

Job Description:

We are looking for an experienced Python Full Stack Developer with strong expertise in Python, Django, React.js, HTML, JavaScript, and RESTful APIs. The ideal candidate should have experience developing scalable web applications, building backend services, and integrating frontend components with backend APIs.

Key Responsibilities:

• Develop and maintain web applications using Python and Django.
• Build responsive user interfaces using React.js, HTML, and JavaScript.
• Design, develop, and integrate RESTful APIs.
• Collaborate with cross-functional teams to deliver high-quality solutions.
• Troubleshoot issues and optimize application performance.
• Python
• HTML
• JavaScript
• React.js
• Django
• RESTful APIs

Job Summary: We are seeking a highly skilled Full-stack Developer to join our dynamic team as a Delivery Module Lead. The ideal candidate will possess strong expertise in Python and front-end technologies, enabling them to design, develop, and maintain robust web applications. This role requires a proactive individual who can collaborate effectively with cross-functional teams to deliver high-quality software solutions that meet business needs.

• Proficient in Python programming language.
• Strong knowledge of front-end technologies such as HTML, CSS, and JavaScript.
• Experience with front-end frameworks like React, Angular, or Vue.js.
• Familiarity with back-end frameworks such as Django or Flask.
• Understanding of RESTful APIs and web services.
• Experience with version control systems, preferably Git.

Company: Wissen Technology

Position: Databricks Engineer

Experience: 6-10 Years

Location: Bengaluru/Mumbai

Employment Type: Full-time

About Wissen Technology

Wissen Technology is a global technology services company focused on delivering innovative software engineering, data, and technology solutions to leading enterprises. The company works with clients across industries to build scalable, high-performance technology platforms and solve complex business and technology challenges.

With a strong focus on engineering excellence, innovation, and collaboration, Wissen Technology brings together skilled technology professionals across areas such as software engineering, data engineering, cloud, analytics, and digital transformation.

At Wissen Technology, employees have the opportunity to work on challenging technology projects, collaborate with experienced engineering teams, and contribute to solutions that create measurable business impact.

Key Responsibilities

• Design, develop, and maintain scalable data processing applications using Python, PySpark, and Spark.
• Develop and optimize data pipelines and workflows on Databricks.
• Collaborate with data engineers, data scientists, business stakeholders, and other technical teams to understand requirements and deliver high-quality solutions.
• Ensure data integrity, quality, performance, and reliability across data processing pipelines.
• Write clean, maintainable, scalable, and efficient code following established coding standards and best practices.
• Perform data analysis and implement appropriate data validation and quality checks.
• Monitor, troubleshoot, and optimize performance issues across data workflows and pipelines.
• Work with relational databases and develop efficient SQL queries for data extraction and transformation.
• Participate in code reviews, testing, deployment, and continuous improvement of data engineering solutions.
• Use Git/version control and follow established software development and deployment practices.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
• Proven experience as a Databricks Developer, Data Engineer, or similar role.
• Strong hands-on expertise in Apache Spark and PySpark.
• Strong programming skills in Python; experience with Scala is an advantage.
• Strong proficiency in SQL and hands-on experience with relational databases.
• Practical experience developing and optimizing data pipelines and data processing applications.
• Familiarity with Git and version control systems.
• Strong understanding of data engineering concepts, data transformation, and data validation.
• Excellent analytical and problem-solving skills.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.

Role Overview

We are looking for an experienced AI/ML Engineer with strong expertise in Python, Generative AI, LLMs, LangChain, and LangGraph. The candidate will be responsible for designing and developing AI-powered applications, intelligent agents, and scalable LLM-based solutions.

Key Responsibilities

• Design and develop AI/ML and Generative AI applications using Python and modern LLM technologies.
• Build LLM-based applications and AI agents using LangChain and LangGraph.
• Develop agentic workflows involving tool calling, memory, reasoning, and multi-step orchestration.
• Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or other foundation models.
• Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases.
• Work with embeddings, prompt engineering, semantic search, and document processing.
• Develop scalable APIs and backend services using Python, FastAPI, or Flask.
• Build and integrate AI solutions with existing applications and enterprise systems.
• Deploy and maintain AI/ML solutions on cloud platforms.
• Collaborate with data scientists, software engineers, and product teams to develop business-focused AI solutions.

Required Skills

• Strong hands-on experience in Python programming.
• Strong experience in AI/ML and Generative AI.
• Hands-on experience with LLMs and LLM-based application development.
• Strong experience with LangChain and/or LangGraph.
• Experience building AI Agents / Agentic AI workflows.
• Strong understanding of RAG, embeddings, vector databases, and prompt engineering.
• Experience with vector databases such as FAISS, Pinecone, Chroma, Weaviate, or Azure AI Search.
• Experience developing REST APIs using FastAPI/Flask.
• Good understanding of Machine Learning, NLP, and deep learning concepts.
• Experience with Azure / AWS / GCP cloud platforms.

Good to Have

• Experience with multi-agent systems and agent orchestration.
• Knowledge of MLOps / LLMOps.
• Experience with Docker, Kubernetes, and CI/CD.
• Knowledge of LLM evaluation, monitoring, observability, and AI governance.
• Experience with Azure OpenAI, Azure AI Foundry, or AWS Bedrock.

Full Stack Developer – AI/ML & GenAI

Location: Mumbai

Experience: 7–9 Years

Employment Type: Full-time

Virtual Drive: Saturday

We are looking for a Python Full Stack Developer with 3+ years of hands-on experience in AI/ML and Generative AI.

Key Skills: Python Full Stack, FastAPI/Flask/Django, React/Angular, AI/ML, GenAI, LLMs, RAG, Embeddings, Vector Databases, Cloud (AWS/Azure/GCP), CI/CD, Docker & Kubernetes.

Key Skills:

• Agentic AI / AI Agents

• Python or Java

• LLMs & Generative AI

• RAG & Vector Databases

• LangChain / LangGraph / AutoGen / CrewAI

• REST APIs & Microservices

• Prompt Engineering

• AI Workflow Automation

Roles & Responsibilities:

• Design and develop AI agents and agentic workflows

• Build scalable backend services using Python or Java

• Integrate LLMs, APIs, tools, and external systems into AI workflows

• Develop RAG-based solutions and intelligent automation

• Design multi-step AI workflows with tool/function calling

• Evaluate, monitor, and optimize AI agent performance

• Collaborate with engineering and product teams to deliver production-ready AI solutions

Key Responsibilities

• Design, develop, and maintain scalable applications using Python.
• Build and integrate AI-powered solutions into existing applications.
• Develop REST APIs and backend services.
• Work with AI/ML models, LLMs, and Generative AI technologies where applicable.
• Integrate AI services and APIs into business applications.
• Write clean, maintainable, and efficient code.
• Collaborate with cross-functional teams to deliver high-quality solutions.
• Troubleshoot issues and optimize application performance.

Must-Have Skills

• Strong hands-on experience in Python development.
• Good understanding of Python frameworks such as FastAPI, Flask, or Django.
• Experience in REST API development and backend services.
• Knowledge or experience in AI/ML concepts.
• Understanding of application development, debugging, and problem-solving.
• Good understanding of databases and data handling.

Good-to-Have Skills

• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with AI APIs and frameworks such as LangChain or LlamaIndex.
• Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, or CI/CD pipelines.

SONiC Forwarding Developer

Experience: 10+ Years

Location: Bangalore / Hyderabad / Delhi / Mumbai

Work Mode: Onsite

Contract Duration: 6 Months

DATA CENTER NETWORKING & SYSTEMS SOFTWARE ENGINEERING

Executive Role Summary

We are seeking an experienced SONiC Forwarding Developer with 10+ years of software engineering expertise in low-level systems programming and networking data plane architectures.

In this role, you will design, develop, and benchmark high-performance forwarding software on the Software for Open Networking in the Cloud (SONiC) operating system. You will collaborate with ASIC hardware vendors and cross-functional teams to engineer line-rate L2/L3 forwarding, ACL, and QoS mechanisms for large-scale data center networks.

1. Key Responsibilities

• Architect, develop, and maintain high-performance network forwarding software using C and C++, with Python and Go tooling.
• Work with switching silicon/ASIC vendors to implement, validate, and tune hardware-specific forwarding features through SAI.
• Design, implement, and debug forwarding pipelines including ACL, QoS, queue scheduling, and traffic shaping.
• Develop L2/L3 packet switching and routing solutions, including firewall integrations, L2VPN and L3VPN.
• Work with data center networking protocols such as BGP, OSPF, EVPN, and VXLAN.
• Profile and optimize software performance, memory utilization, cache locality, and latency.
• Collaborate with hardware, QA, and network operations teams for testing, debugging, and product delivery.

SAO Orchestration – NSO Profile

Job Title: SAO Orchestration – NSO Profile

Experience: 5+ Years

Location: Bangalore / Hyderabad / Mumbai / Delhi

Work Mode: Onsite

Contract Duration: 6 Months

Job Description

We are looking for an experienced SAO Orchestration / Cisco NSO Engineer with strong expertise in network automation, service orchestration, and software development.

Key Responsibilities

• Design and develop network service orchestration solutions using Cisco NSO.
• Develop and maintain YANG-based service models.
• Build network automation workflows using Python.
• Develop and integrate REST APIs for network and service orchestration.
• Work with Kubernetes (K8s) and containerized environments.
• Automate network configuration and service provisioning across multi-vendor environments.
• Integrate orchestration platforms with network devices and external systems.
• Troubleshoot and resolve issues related to network automation and orchestration.
• Collaborate with network, software, and infrastructure teams.

Role: Full Stack Engineer

Location: Hyderabad/Mumbai/Bangalore/Gurgaon

Required Experience: 4-7 years

Role Summary:

We are looking for Software Engineers with deep experience in building highly scalable and reliable enterprise applications. We are looking for engineers who have experience building cloud based/cloud native solutions from scratch. This includes demonstrable expertise in an enterprise friendly backend framework. We expect the engineer to work in a team consisting of Project Managers, Designers, Data Scientists and Software Architects. This is an exciting opportunity to work in a fast paced and innovative environment along with a group of world class and entrepreneurial professionals.

Responsibilities:

• Design and develop user-friendly web interfaces using HTML, CSS, and JavaScript.

• Utilize modern frontend frameworks and libraries such as React, Angular, or Vue.js to build dynamic and responsive web applications.

• Develop and maintain server-side logic using programming languages such as Java, Python, Ruby, Node.js, or PHP.

• Build and manage APIs for seamless communication between the frontend and backend systems.

• Integrate third-party services and APIs to enhance application functionality.

• Implement CI/CD pipelines to automate testing, integration, and deployment processes.

• Monitor and optimize the performance of web applications to ensure a high-quality user experience.

• Stay up-to-date with emerging technologies and industry trends to continuously improve development processes and application performance.

Qualifications:

• Bachelors/Masters in Computer Science or related subjects or hands-on experience demonstrating working understanding of software applications.

• Knowledge of building applications that can be deployed in a cloud environment or are cloud native applications.

• Strong expertise in building backend applications using Java/C#/Python with demonstrable experience in using frameworks such as Spring/Vertx/.Net/FastAPI.

 • Deep understanding of enterprise design patterns, API development and integration and Test-Driven Development (TDD)

• Working knowledge in building applications that leverage databases such as PostgreSQL, MySQL, MongoDB, Neo4J or storage technologies such as AWS S3, Azure Blob Storage.

• Hands-on experience in building enterprise applications adhering to their needs of security and reliability.

• Hands-on experience building applications using one of the major cloud providers, preferably GCP.

• Working knowledge of CI/CD tools for application integration and deployment.

• Working knowledge of using reliability tools to monitor the performance of the application.

Job Summary:

Wissen Technology is hiring an AI Implementation Engineer to build, deploy, and scale enterprise-grade Generative AI solutions across business-critical applications. The role involves developing production-ready AI systems using Azure AI services, Large Language Models (LLMs), RAG architectures, and agent-based frameworks while collaborating closely with engineering teams to drive AI adoption and innovation.

Experience

6-12 years

Location

Mumbai / Bangalore

Mode of Work

Hybrid

Mandatory Skills (Must Have)

• Python programming (6+ years) including asynchronous programming and backend application development

• Java and Spring Framework (3+ years) for enterprise-scale application integration

• Azure OpenAI Service, Azure AI Foundry, and Azure AI Search for production GenAI applications

• Retrieval Augmented Generation (RAG) architecture including embeddings, chunking, vector databases, reranking, and grounding techniques

• Agent Frameworks such as Microsoft Agent Framework, Semantic Kernel, AutoGen, LangChain, or LangGraph

• Snowflake and Cortex AI (Cortex Search, LLM Functions) with strong SQL expertise

• Prompt Engineering, LLM evaluation frameworks, testing, and model performance optimization

• DevOps and Cloud Deployment using Azure DevOps, GitHub Actions, Docker, AKS, Azure Functions, and observability tools

Optional Skills (Good to Have)

• React.js for AI-powered user interfaces and conversational applications

• Azure AI Content Safety and Responsible AI implementation experience

• Financial Services, Banking, or other regulated industry domain experience

• Real-time streaming applications and token-level LLM operations

• Performance optimization, caching strategies, and cost optimization for AI workloads

• Microsoft Azure AI Engineer Associate Certification

Must-have qualifications 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production. Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design. Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow. Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling. RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding. Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data. Prompt engineering as versioned code; building and running evaluations. DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability. Preferred Financial services or other regulated environments. Front-end (React) for AI-assisted UX; streaming and tokenlevel operations. Azure AI Content Safety and responsible-AI practices. Certification: Azure AI Engineer Associate. What success looks like - first 6 to 12 months Multiple GenAI features shipped to production within the embedded delivery pods. Measurable adoption and productivity uplift in the teams you support. Reusable components adopted from the architects' reference framework. Clear contributio

Senior AI Engineer

Code Generation, Agent Architecture & LLM Systems

📍 Mumbai (On-site) | Full-time | 5+ 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.

We are hiring a Senior AI Engineer for a dedicated client engagement focused on building an AI-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code.

The mandatory requirement for this role is hands-on production experience shipping LLM-powered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage.

The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy.

You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent Architecture

Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions.

Make and revisit architectural decisions on single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair sub-agents.

Code Generation Pipeline

Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit.

Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies.

Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-Repair Loop

Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation.

This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context Management

Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval.

Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes.

Own token budgeting and prompt caching strategy.

Prompt Engineering as a Discipline

Own the system prompt and per-task prompt variants (new feature, bug fix, styling change).

Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites.

Version prompts like code with changelogs and rollback capability.

Evaluation and Quality Measurement

Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant.

Define regression gates that block quality-degrading changes from shipping.

Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time.

This responsibility is non-negotiable at this level.

Model Strategy and Cost

Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation.

Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection.

Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and Reliability of Agent Behaviour

Defend against prompt injection from user content and fetched web content.

Ensure secrets never appear in generated client code.

Define what the agent's tools may and may not do in collaboration with the platform team.

Contribute to output moderation and abuse-pattern awareness.

Mentorship and Engineering Standards

Run code reviews, define engineering conventions for AI work, and raise the engineering bar across the AI team.

Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on Production Ownership of LLM-Powered Systems with Agent Architectures (Mandatory)

Must have personally shipped and operated at least one complex production AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.

POCs, internal demos, and tutorial-grade work do not qualify.

5+ Years of Professional Software or AI Engineering Experience

With at least 3 years focused on LLM applications, AI engineering, or production AI systems.

Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python Proficiency and Service Development

Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging.

Not notebook-only.

Depth Across LLM APIs and Agent Systems

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

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

Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, Systematic Evaluation Practice - Non-Negotiable

Must have built evaluation harnesses that gate production releases, not ad-hoc testing.

Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval.

Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost Discipline for Production AI

Track record of measurable cost optimisation on production AI features.

Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS Working Knowledge

Hands-on with EC2, S3, IAM, and Docker.

Comfort with CI/CD workflows and deploying AI services.

Awareness of LLM Security Failure Modes

Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to Have

• Experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work
• MCP server authoring
• Open-source AI contributions
• Published technical writing on LLM systems
• Multi-modal model experience
• Fine-tuning exposure (LoRA, QLoRA, PEFT)

Job Description: Senior Java/Python Developer (AI & GenAI Specialist)

Location

Position Summary

We are seeking an experienced Senior Java/Python Developer with strong expertise in enterprise application development and extensive hands-on experience in Artificial Intelligence (AI), Generative AI (GenAI), Large Language Models (LLMs), and AI-powered application development. The ideal candidate will lead the design, development, and deployment of scalable, intelligent solutions that integrate modern AI technologies with enterprise-grade Java and Python ecosystems.

This role requires a combination of strong software engineering skills, AI innovation capabilities, and architectural leadership.

Key Responsibilities

• Application Development

• Design, develop, and maintain scalable enterprise applications using Java and Python.

• Develop RESTful APIs, microservices, and event-driven architectures.

• Build high-performance backend systems using Spring Boot, FastAPI, Flask, or Django.

• Ensure code quality through unit testing, integration testing, and code reviews.

AI & Generative AI Development

• Design and implement AI-powered solutions leveraging Large Language Models (LLMs).

• Develop intelligent applications using OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and similar platforms.

• Build Retrieval Augmented Generation (RAG) architectures for enterprise knowledge systems.

• Implement AI agents, copilots, chatbots, virtual assistants, and workflow automation solutions.

• Engineer prompts and build prompt orchestration frameworks.

• Develop multi-agent AI systems and autonomous AI workflows.

Required Technical Skills

Core Programming

• Expert-level proficiency in:

o Java (Java 11/17/21)

o Python 3.x

• Strong understanding of OOP, design patterns, and software engineering principles.

Java Technologies

• Spring Boot

• Spring Cloud

• Hibernate/JPA

• Microservices Architecture

• Kafka/RabbitMQ

• REST API Development

Python Technologies

• FastAPI

• Flask

• Django

• Pandas

• NumPy

• Async Programming

Generative AI & LLMs

• OpenAI APIs

• Azure OpenAI

• LangChain

• LangGraph

• LlamaIndex

• Semantic Kernel

• Hugging Face

• Prompt Engineering

• RAG Frameworks

• AI Agent Frameworks

• Vector Databases (Pinecone, Weaviate, ChromaDB, Milvus, FAISS)

Preferred Qualifications

• Experience developing enterprise AI copilots and intelligent assistants.

• Experience implementing AI solutions using Microsoft Copilot Studio, Azure AI Services, or similar platforms.

• Knowledge of AI governance, responsible AI, security, and compliance frameworks.

• Experience in travel, finance, telecom, retail, or large enterprise environments.

• Exposure to graph databases and knowledge graphs.

• Understanding of multimodal AI (text, image, audio, video).

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related discipline.

• Generative AI certifications preferred.

Key Competencies

• Solution Architecture

• AI Innovation & Thought Leadership

• Problem Solving

• Stakeholder Management

• Technical Mentoring

• Agile Development

• Analytical Thinking

• Communication & Presentation Skills

Success Metrics

• Delivery of scalable AI-enabled enterprise solutions.

• Reduction in operational effort through AI automation.

• Successful deployment of GenAI applications into production.

• Application performance, reliability, and security.

• Adoption of AI best practices across development teams.

Experience: 4+ Years 

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Role Summary:

AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role — ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered innovation.

Responsibilities:

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption

• Lead solutioning and integration for complex data workflows (batch and streaming)

• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging

• Implement robust data quality, testing, lineage, and governance frameworks

• Drive best practices across pipeline performance, reusability, and scalability

• Mentor junior engineers and contribute to capability building within the data team

Requirement:

• 4+ years of experience in data engineering, with expertise in:

      o End-to-end pipeline development (batch and streaming)

      o Data modeling (dimensional, Data Vault, OBT)

      o ETL/ELT design patterns, performance tuning, and optimization

      o SQL (Advanced) and Python (Advanced)

      o Apache Spark for large-scale data processing

• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality

• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows

• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI

• Exposure to finance or sales data domains

• Familiarity with Databricks, Delta Lake, or Apache Iceberg

• GCP Professional Data Engineer certification is a plus

EMBEDDED AI ENGINEERING POD

AI Implementation Engineer Role

Level: AI Implementation Engineer Senior / Advanced - 6+ years

Practice: Wissen GenAI

Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams

Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead

Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.

You deliver production software and help the teams you join work faster.

As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.

Key responsibilities

1. Build and ship.

Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.

2. Embed and enable.

Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.

3. Productionize.

Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.

4. Integrate securely.

Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.

5. Iterate on quality.

Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.

6. Measure.

Track delivery and quality metrics that roll up to the program's targets.

Must-have qualifications

• 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
• Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
• Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
• Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.

Preferred

• RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
• Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
• Prompt engineering as versioned code; building and running evaluations.
• DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
• Financial services or other regulated environments.
• Front-end (React) for AI-assisted UX; streaming and token level operations.
• Azure AI Content Safety and responsible-AI practices.
• Certification: Azure AI Engineer Associate.

What success looks like - first 6 to 12 months

• Multiple GenAI features shipped to production within the embedded delivery pods.
• Measurable adoption and productivity uplift in the teams you support.
• Reusable components adopted from the architects' reference framework.
• Clear contribution to faster time-to-market and lower defect rates.

Must of Skills/Experience 

• System Design

• Python

• TensorFlow

• Google ADK or Lang Graph

• Lang Chain , Lang Graph

• Spark

• Agentic AI Design

• ML Ops

• MCP (client and server)

• FastAPI

• Doc Factory

• RAG

• Golang

• LLMs – Gemini, Open AI

• NLP

• Dev Assistant - AI based code - generation

(Qwen or Claude or Copilot)

• CI/CD

• Good in oral and written communication,

collaboration and be a team player

Good to have skills 

• DevOps with K8

• Scripting

• Java

• REST API

• UV

• ReACT

• DocFactory

• Unix

Responsibilities

·        Build and operate the agentic loop: trigger → orchestration → agent execution → output to JIRA → human accept/reject → next agent, across design, coding, review, and testing agents.

·        Implement model routing and retry logic across a provider-agnostic model layer (e.g., Claude via AWS Bedrock, self-hosted or alternative models as cost/sovereignty hedges), including business-continuity fallback if a given provider becomes unavailable.

·        Own token cost control and context window management — per-agent and per-run budgets, circuit breakers that halt runaway execution, and cost observability tied back to JIRA.

·        Stand up and maintain observability, alerting, and monitoring across the agent fleet (e.g., Langfuse or equivalent), so agent health, cost, and quality are visible in real time.

·        Implement agent governance and safety guardrails: deterministic pre/post hooks gating every LLM call, kill switches, prompt injection prevention and mitigation, and audit logging.

·        Integrate the harness with JIRA as the system of record and other business systems as needed, ensuring every agent action, decision, and human override is tracked with no side channels.

·        Pair directly with client engineers throughout — this is capability transfer, not black-box delivery. You'll document, demo, and hand over as you build.

·        Work in outcome-based delivery stages (spike → architecture sign-off → build → pilot) with gated milestones tied to working software demos, not fixed artifact checklists.

·        Participate actively in team discussion and design decisions — this team expects engineers to challenge ideas constructively and speak up, not defer silently.

Must-Have Experience

·        Hands-on production experience building agentic systems(not tutorial-level or personal-project experience.) Candidates should be able to speak concretely about systems they've shipped.

·        Practical experience with agentic frameworks such as LangChain, LangGraph, or equivalent orchestration frameworks.

·        Experience with LLM orchestration and model routing across multiple providers/models, including fallback and retry design.

·        Working knowledge of agent governance: guardrails, human-in-the-loop approval flows, kill switches, and audit trails.

·        Practical understanding of prompt injection risks and mitigation techniques.

·        Experience with token cost management and context window/memory handling at production scale — this is a named governance requirement for the engagement, not a nice-to-have.

·        Strong Python (or equivalent) engineering background, comfortable working in AWS environments (Bedrock/AgentCore exposure a strong plus).

·        Experience with observability/monitoring tooling for distributed or agentic systems (e.g., Langfuse, Datadog, or equivalent).

·        Comfortable working with JIRA/Atlassian APIs or similar ticketing-system-of-record integrations.

Nice to Have

·        Direct experience with AWS Bedrock AgentCore, Temporal (or similar workflow orchestration), or LiteLLM-style model gateways.

·        Exposure to Cursor or other AI-native IDEs in a production engineering context.

·        Experience with self-hosted open-weight models (e.g., DeepSeek, GLM) as cost or sovereignty hedges alongside commercial APIs.

·        Financial services or other regulated-industry background.

·        Familiarity with Claude Code, Claude Cowork, or Claude Skills.

Qualifications

·        Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

·        3-5+ years in software/platform engineering, with a meaningful portion of that time specifically on agentic or LLM-orchestration systems (not general ML or data engineering alone).

Relevant Experience

·        Already built this kind of system and can talk through the trade-offs from experience, not theory.

·        Comfortable operating with ambiguity - technology choices (frameworks, specific models, tooling) are expected to evolve during the engagementand milestones are tied to outcomes rather than fixed deliverables.

·        Will contribute opinions - quiet execution without a point of view is not a fit for this team.

Senior Xano Developer

Visual Backend Development, APIs & AI-Assisted Build

📍 Mumbai (On-site) | Full-time | 3-5 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.

We are hiring a Xano Developer who will build backend systems and APIs for our customer engagements on Xano, the visual backend development platform.

The mandatory requirement for this role is hands-on production backend engineering experience, including PostgreSQL data modelling and REST API design, in either a Node.js or Python environment.

Prior production work on Xano is strongly preferred.

The role is hands-on and customer-facing. You will own backend delivery across engagements: designing data models, building API flows in Xano, integrating third-party services, and partnering with frontend, mobile, and AI engineers on contracts and behaviour.

The work spans all three Xano build modes: no-code function stacks, custom code through Xano’s scripting and code blocks, and Xano’s AI assistance and agentic features.

A typical week includes a data model review for a new engagement, building a complex API flow in Xano, integrating a third-party webhook, and a customer working session on a new module.

Responsibilities:

Backend Delivery on Xano

Own end-to-end backend implementation on Xano: database schema, API endpoints, function stacks, background tasks, and integrations.

Ship production-ready work that meets customer requirements and engineering quality standards.

Build Across All Three Xano Modes

Use Xano’s no-code function stacks for standard CRUD and business logic.

Drop into custom code (JavaScript, Python through code blocks, expressions) where visual flows would be unwieldy.

Use Xano’s AI assistance and agentic features to accelerate routine build work.

Database Design on PostgreSQL

Own data model decisions for each engagement: table design, relationships, indexes, addons, and query performance.

Make schema choices that hold up as product usage grows and that map cleanly to the API contracts the client needs.

API Design and Integration

Design clean REST API contracts that the frontend, mobile, and third-party consumers can rely on.

Cover authentication, input validation, pagination, error handling, and rate limiting.

Integrate external services (payment gateways, messaging, storage, AI providers) through Xano’s connectors and custom requests.

Product Thinking and Solutioning

Translate fuzzy product asks from customers into concrete backend solutions.

Ask the right questions about edge cases, data lifecycle, multi-tenancy, and access control before building.

Push back on requirements that will cause pain later.

Customer Communication

Work directly with customers in discovery, design reviews, demos, and weekly working sessions.

Explain trade-offs in plain language, present options with clear recommendations, and write tight technical updates.

AI-Assisted Backend Development

Use Xano’s built-in AI features as well as external AI tools (Claude, Cursor, and similar) day to day for schema drafts, function stack scaffolding, query writing, integration setup, and review.

Develop strong instincts for when AI output is usable as-is and when it must be reworked.

Quality, Testing, and Reliability

Test the flows you ship.

Set up sensible error handling, logging, and alerts for the backend services you own.

Participate in incident response when something breaks in production.

Documentation and Handover

Document data models, API contracts, and non-obvious decisions inside Xano and in shared docs so the rest of the team and the customer can pick up the work without you in the room.

Continuous Learning

Track changes to the Xano platform, including new features, performance improvements, and AI capabilities.

Apply them to active engagements where they reduce build effort or improve product outcomes.

Requirements:

Hands-on Production Backend Engineering Experience (Mandatory)

Must have personally shipped backend systems to production for real users, with ownership of API design and data modelling.

POCs, coursework, and internal-only tools do not qualify.

3 to 5 Years of Professional Backend Engineering Experience

In either a Node.js or Python environment.

Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

Strong PostgreSQL Skills

Schema design, indexing, query writing, and migrations on at least one production system.

Able to reason about query performance and design data models that hold up under realistic product usage.

REST API Design and Integration Depth

Comfort designing API contracts that are clean, predictable, and easy for frontend, mobile, and third-party consumers to work with.

Experience integrating external services such as payment gateways, messaging providers, storage, and AI APIs.

Familiarity with at Least One Node.js or Python Backend Stack

Such as Express, NestJS, Fastify, FastAPI, Django, or Flask.

Comfort reading and writing application code outside of visual environments when the situation calls for it.

Product Thinking and Solutioning

Ability to take a fuzzy product brief, ask the right questions, and propose a backend design that is fit for purpose.

Strong instincts for what to build first, what to defer, and what not to build.

Strong Written and Spoken English Communication

Confident in customer working sessions and design reviews.

Comfortable writing precise technical documentation and explaining trade-offs to non-engineering stakeholders.

Cloud and Deployment Fundamentals

Working knowledge of at least one of AWS, GCP, or Azure: deploying services, reading logs, managing environments, and basic operational tasks.

Familiarity with Docker is a plus.

Bachelor’s Degree

Bachelor’s degree in Computer Science, Information Technology, or a related engineering discipline.

Exceptional candidates with demonstrable production experience and strong portfolios may be considered without a formal degree.

Nice to Have

• Prior production experience on Xano, Bubble, Retool, or comparable visual or low-code backend platforms
• Full stack experience with React, Next.js, React Native, or Flutter
• Experience integrating LLM APIs (OpenAI, Anthropic, Google) into backend workflows
• Multi-tenant SaaS product experience
• Prior agency, consulting, or product-engineering experience

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.

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.

Role Overview

As an AI Quality Engineer, you will be the strategic lead for quality within our AI-driven product ecosystem. You will be responsible for validating non-deterministic AI outputs and microservices. You will use tools like Claude Code, Cursor, and Gemini, moving from manual oversight to high-velocity, AI-augmented delivery. You will ensure that our AI products are not only functional but reliable, ethical, and scalable.

Core Responsibilities

• AI-First Test Strategy & Planning: Define and implement the end-to-end test strategy for major AI product areas.
• AI-Augmented Automation: You will adopt Cursor and Claude Code to refactor existing frameworks, develop new frameowrk, migrate legacy framework to modern technologies and automate the creation of test suites.
• Defect Management & Root Cause Analysis: You will perform Root Cause Analysis, submit bugs and ensure their timely resolution.
• Documentation & Reporting: You will document your work and report on quality metrics to stakeholders.

Required Qualifications

• AI Toolchain Mastery: Expert-level experience using AI coding assistants (Claude Code, Cursor) and LLMs (Gemini, GPT-4) to accelerate the SDLC.
• SDLC Experience: Proven track record of product delivery in an Agile environment with a focus on CI/CD (ADO and GitHub Actions).
• Technical Stack: Proficiency in C#, Python or JavaScript and experience with modern testing frameworks (e.g., Selenium, Playwright, Nunit, PyTest).
• Autonomy: Ability to create cases, execute tests manually and automate with minimal oversight.
• Education/Experience: 2-3 years in Quality Engineering with a focus on Web and Mobile Applications testing.

Role Summary

We are seeking a skilled GenAI & Agentic AI Engineer with strong experience in building end‑to‑end AI/ML solutions, Generative AI applications, and agent‑based automation workflows. The ideal candidate will have a solid background in machine learning along with hands‑on expertise in LLMs, RAG, embeddings, vector databases, and Agentic AI frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.

Key Responsibilities

• Build and deploy GenAI applications using LLMs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.).
• Develop Agentic AI workflows using frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.
• Design and implement RAG pipelines, vector search solutions, and embedding‑based retrieval systems.
• Build scalable AI services using Python, FastAPI/Flask, and cloud platforms (Azure/AWS/GCP).
• Collaborate with cross‑functional teams to define use cases and convert them into production‑ready GenAI solutions.
• Implement hallucination reduction, prompt‑engineering strategies, and model evaluation methods.
• Integrate LLMs with enterprise applications, APIs, and automation workflows.
• Work with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search.
• Monitor, evaluate, and optimize GenAI models for accuracy, performance, and cost.

Required Skills & Experience

• 5+ years of experience in AI/ML, including model development, data preprocessing, EDA, training, and evaluation.
• 2+ years of hands‑on experience in Generative AI (LLMs, embeddings, RAG, LLM‑based apps).
• 6+ months of hands‑on experience with Agentic AI frameworks (CrewAI / AutoGen / LangGraph / LangChain Agents).
• Strong proficiency in Python and ML libraries (Scikit‑learn, Pandas, NumPy).
• Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt engineering.
• Familiarity with building scalable APIs using FastAPI, Flask, or Django.
• Hands‑on knowledge of cloud services (Azure/AWS/GCP) for AI deployment.
• Strong understanding of REST APIs, microservices, and integration patterns.
• Experience with Git, CI/CD, Docker, and model deployment best practices.

WE'RE HIRING

Forward Deployed Engineer (FDE) – AI Solutions

Location: Mumbai (On-site with Clients) | Salary: ₹30,000 – ₹50,000/month | Full-Time

Position

Forward Deployed Engineer (FDE)

Location

Mumbai (physical presence at client sites required)

Salary

₹30,000 – ₹50,000 per month (entry-level / fresher range, based on skill)

Job Type

Full-time, On-site / Client-facing

Preferred Background

CSE / IT / related engineering graduates

Eligibility

Open to all ages who meet the skill requirement

About the Role

We are looking for a Forward Deployed Engineer (FDE) to work directly at client sites across Mumbai, deploying, customizing, and supporting our AI-powered solutions. This role sits at the intersection of engineering and client relationships — you'll write/adapt code, configure AI systems on the ground, troubleshoot real-time issues, and translate technical concepts into simple language for clients. Ideal for a CSE/IT graduate who is strong in tech, genuinely curious about AI, and enjoys solving problems face-to-face with clients rather than purely behind a desk.

Key Responsibilities

-Travel to client sites across Mumbai to deploy, configure, and customize AI-based solutions

-Debug and resolve technical issues on-site, escalating complex problems to the core engineering team when needed

-Write scripts/code to integrate, adapt, or fine-tune AI tools/models for specific client use cases

-Explain technical concepts and AI capabilities clearly to non-technical stakeholders

-Gather client requirements and feedback, and relay them back to the product/engineering team

-Document deployments, issues, and solutions for future reference

Requirements

CSE / IT / Computer Engineering degree strongly preferred

Solid understanding of AI/ML concepts and tools (LLMs, APIs, automation, Python-based AI tooling, etc.)

Working knowledge of at least one programming language (Python preferred)

Excellent verbal communication skills — comfortable explaining technical topics to clients

Strong problem-solving ability and comfort working independently on-site

Quick learner, adaptable to new tools/tech stacks

Willingness to travel daily within Mumbai for client visits

Open to all age groups — skills and attitude matter more than age

Perks

Travel/conveyance allowance

Direct hands-on exposure to real-world AI deployments

Performance-based growth and incentives

Mentorship from core engineering team

- Design, develop, and maintain full stack web applications using Python (backend) and modern frontend frameworks

- Build and integrate REST APIs; work with databases (SQL/NoSQL)

- Apply AI/ML concepts or tools within applications (e.g., model integration, LLM APIs, data-driven features)

- Collaborate with cross-functional teams on financial/trading platform features

- Write clean, scalable, well-tested code; participate in code reviews

- Troubleshoot and optimize application performance

Job Title : Senior Software Engineer (Python, Golang, Node.js, Elixir, SQL)

Experience : 5+ Years

Location : Mumbai (Work From Office)

Employment Type : Full Time Opportunity

Job Summary :

We are looking for a Senior Software Engineer with strong backend development experience to build scalable, cloud-native applications and distributed systems.

The ideal candidate should have experience in product-based environments, designing microservices, REST APIs, and customer-facing production applications while collaborating with cross-functional teams.

Mandatory Skills :

Backend Development, Python, Golang, Node.js, Elixir, SQL, Cloud-Native Architecture, REST APIs, Microservices, Distributed Systems, Cloud Platforms, Relational & NoSQL Databases, Platform Engineering, CI/CD, Production Support, System Design

Key Responsibilities :

• Design and develop scalable backend services, REST APIs, and microservices.
• Build and enhance cloud-native, high-performance applications.
• Participate in architecture and system design discussions.
• Collaborate with Product, DevOps, Security, and Data Engineering teams.
• Troubleshoot production issues and optimize application performance.
• Mentor team members and contribute to engineering best practices.

Required Skills :

• 5+ years of software development experience in product-based organizations.
• Strong backend development using Python, Golang, Node.js, Elixir, or similar technologies.
• Experience with REST APIs, Microservices, SQL, and Distributed Systems.
• Strong understanding of cloud platforms and cloud-native architecture.
• Hands-on experience with relational and NoSQL databases.
• Familiarity with CI/CD, monitoring, and DevOps practices.

Preferred Skills :

• Experience building highly scalable distributed systems.
• Strong debugging, troubleshooting, and performance optimization skills.
• Familiarity with DevOps practices, CI/CD pipelines, monitoring, logging, and observability tools.
• Excellent communication, collaboration, and problem-solving abilities.
• Experience mentoring engineers and leading technical initiatives.

We are looking for an exceptional Python Backend Developer to join our engineering team. You will be responsible for managing the interchange of data between the server and the users, developing server-side logic, and ensuring high performance and responsiveness to requests from the front end. The ideal candidate must have a rock-solid foundation in core computer science concepts, specifically Object-Oriented Programming (OOP) and Data Structures and Algorithms (DSA), to design and implement highly scalable and optimised backend systems.

Responsibilities:

• Design, build, and maintain efficient, reusable, and reliable Python code.
• Develop robust, highly scalable, and low-latency backend architectures and APIs.
• Apply strong OOPS principles to build modular and maintainable software systems.
• Utilise advanced Data Structures and Algorithms (DSA) to solve complex computational problems and optimise application performance.
• Integrate user-facing elements developed by front-end developers with server-side logic.
• Implement security and data protection measures.
• Identify bottlenecks, troubleshoot bugs, and devise elegant solutions to mitigate these issues.
• Collaborate cross-functionally with product managers, front-end developers, and QA engineers to deliver high-quality features.

Requirements:

• Core Python: Strong proficiency in Python programming with a deep understanding of its quirks, ecosystem, and best practices.
• OOPs Expertise: Excellent command over Object-Oriented Programming concepts (Inheritance, Polymorphism, Encapsulation, Abstraction) and design patterns.
• DSA Proficiency: Strong problem-solving skills with a deep understanding of Data Structures (Arrays, Trees, Graphs, Hash Tables, etc. ) and Algorithms (Sorting, Searching, Dynamic Programming, etc. ).
• Frameworks: Hands-on experience with popular Python web frameworks such as Django, FastAPI, or Flask.
• Database Management: Solid understanding of relational databases (e. g., PostgreSQL, MySQL) and ORM (Object-Relational Mapper) libraries.
• API Development: Experience in designing and developing RESTful APIs.
• Version Control: Proficient understanding of code versioning tools, such as Git.
• Clean Code: A strong commitment to writing clean, readable, and properly documented code.

Good to Have (Optional):

• Experience with NoSQL databases (e. g., MongoDB, Redis).
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
• Knowledge of asynchronous programming in Python (asyncio).

Job Title : Senior Software Engineer

Experience : 5+ Years

Location : Mumbai (Work from Office)

Notice Period : Immediate to 15 Days

Mandatory Skills :

Platform Engineering, Backend Development, Python/Golang/Node.js/Elixir, Microservices, REST APIs, Cloud-Native Architecture, Distributed Systems, SQL, Cloud Platforms (AWS/Azure/GCP), Product-Based Experience

Role Overview :

We are looking for a Senior Software Engineer with strong backend engineering expertise to design, build, and scale cloud-native platform services. The ideal candidate should have experience working in product-based organizations, building highly scalable distributed systems, and contributing to platform engineering initiatives.

You will work closely with Product, DevOps, Security, and Engineering teams to build reliable, secure, and high-performance backend systems while driving technical excellence across the organization.

Key Responsibilities :

• Design, develop, and enhance core platform modules and shared backend services.
• Build scalable REST APIs, backend services, and data pipelines for high-volume production environments.
• Participate in architecture discussions and contribute to technical design decisions.
• Collaborate with Product, DevOps, Security, and Data Engineering teams to deliver scalable solutions.
• Design systems with a focus on scalability, performance, security, maintainability, and reliability.
• Troubleshoot complex production issues and implement permanent solutions.
• Review code, mentor engineers, and promote engineering best practices.
• Improve platform reliability, observability, and developer productivity.
• Drive continuous improvements in coding standards, architecture, and development processes.

Required Skills & Qualifications :

• 5+ years of software development experience in product-based companies (B2B experience preferred).
• Strong backend development experience using one or more of :
• Python
• Golang
• Node.js
• Elixir
• Hands-on experience with Microservices Architecture.
• Strong understanding of Cloud-Native Application Development.
• Experience designing and developing RESTful APIs and backend services.
• Minimum 3 years of experience working on cloud-based, customer-facing production applications.
• Strong knowledge of Distributed Systems Design.
• Experience with relational and NoSQL databases.
• Good understanding of SQL and data modeling.
• Experience designing reusable platform services consumed by multiple engineering teams.
• Strong product mindset with the ability to balance business requirements and technical excellence.
• Backend-focused engineer with exposure to frontend technologies.

Preferred Skills :

• Experience building highly scalable distributed platforms.
• Strong debugging and performance optimization skills.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with DevOps practices, CI/CD pipelines, monitoring, logging, and observability tools.
• Excellent analytical, communication, and problem-solving skills.
• Experience mentoring engineers and driving technical initiatives.

Preferred Background :

• Product-Based Organization
• Platform Engineering Team
• FinTech or B2B SaaS products (preferred)

Job Summary

We are seeking a highly skilled and experienced Senior Salesforce QA Engineer to lead the end-to-end quality assurance for our enterprise Salesforce platform. In this role, you will design robust test strategies, establish automated testing pipelines, and validate complex custom configurations, Apex code, and integrations. As a senior member of the team, you will bridge the gap between business requirements and technical execution, ensuring the delivery of high-quality, scalable solutions across Sales, Service, and Custom Clouds.

Key Responsibilities

• Test Strategy & Planning: Define, implement, and maintain comprehensive test strategies, test plans, and test cases covering functional, regression, integration, and end-to-end scenarios.

• Test Automation: Architect, scale, and maintain automated testing frameworks using enterprise tools (e.g., Provar, Tricentis Tosca, or Selenium with Java/Python) specifically optimized for Salesforce's dynamic UI.

• Complex Custom Validation: Validate complex programmatic customizations (Apex classes, Triggers, Lightning Web Components) and declarative features (Advanced Flows, Validation Rules).

• Integration Testing: Lead end-to-end API testing (REST/SOAP) to verify seamless data flow between Salesforce and upstream/downstream external systems.

• Environment & Release Management: Oversee sandbox deployments, data masking, and regression testing during Salesforce seasonal releases and monthly deployment cycles.

• Defect Lifecycle Management: Own the defect tracking process in Jira or Azure DevOps, collaborating closely with developers, business analysts, and product owners for rapid root-cause resolution.

• Mentorship & Leadership: Provide technical guidance and mentorship to junior QA engineers and lead user acceptance testing (UAT) phases with business stakeholders.

Required Technical Skills & Qualifications

• Experience: 5 to 10 years of dedicated software quality engineering experience, with a minimum of 3+ years focused exclusively on testing Salesforce ecosystems.

• Salesforce Core Knowledge: Deep understanding of Salesforce architecture, data models, object relationships, sharing rules, and platform governor limits.

• Automation Expertise: Hands-on experience developing framework code or no-code architectures using tools like Provar, Selenium WebDriver, Tricentis Tosca, or UFT.

• API Testing: Proficient in API testing tools such as Postman, SoapUI, or automated API frameworks.

• Agile & Devops: Strong experience working within Agile/Scrum methodologies and integrating automated tests into CI/CD pipelines (e.g., Copado, Jenkins, GitHubActions).

• Data Management: Proficiency in writing SQL queries and utilizing Salesforce Data Loader for test data creation and verification.

We’re looking for a hands-on builder who can thrive in a fast-paced startup environment. You’ll own features end-to-end, from designing architecture to writing clean, reusable code, testing, deploying, and iterating fast.

What you’ll do

• Build and scale web + mobile applications using Python (Django) and React Native/React.
• Design, develop, and deploy cloud-native solutions using AWS services.
• Work with both SQL and NoSQL databases (PostgreSQL, DynamoDB).
• Ensure applications are secure, scalable, and performance-optimized.
• Collaborate closely with product, design, and business teams to ship features at lightning speed.
• Take ownership of problems - from brainstorming and architecture to debugging in production.
• Bring startup energy: move fast, learn fast, and don’t be afraid to get your hands dirty.

What we’re looking for

• 1-3 years of experience in full-stack development.
• Strong experience in Python (Django).
• Proficiency in React Native/React, with solid knowledge of JavaScript.
• Experience with AWS services (serverless, EC2, S3, etc.).
• Experience with docker or kubernetes.
• Hands-on with databases: PostgreSQL, DynamoDB.
• Strong understanding of data structures, design patterns, and microservices architecture.
• Proficiency with Git and version control workflows.
• A product-first mindset, balancing code quality with speed of execution.
• Great communication skills, detail-oriented, and a true team player.
• Bonus - If you are an AI native developer and try to solve problems using AI

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time 

We're building in a market that hit $47B in 2026 and is on track to hit $107.5B by 2028 and we're not chasing that opportunity from the sidelines. Our founding team brings marketing expertise from Kotak and Amazon paired with deep AI chops, we were selected as one of just 20 startups by Google, and we already have paying customers like Kotak and Myntra using the product in production. Join us early and help build the infrastructure that turns AI marketing adoption (already at 88%) into real, scaled results for customers who are already paying for it, not case studies.

Founding Product Engineer, Applied AI

Location: Mumbai • Hybrid • Reports to: CTO

WHAT THIS ROLE ACTUALLY IS

Weve built a multi-agent AI system for marketing. It works well out of the box but every client (their data, workflows, brand rules, compliance constraints, output preferences) is different. Generic doesnt ship results. Customised does.

This role is the bridge: you sit between our agent architecture and the client’s reality. You understand both deeply, and you make the agents do what each specific client needs them to do.

Think Palantir Forward Deployed Engineer, but for AI agents. An engineer who owns product outcomes end-to-end.

WHAT YOU'LL DO

Day-to-day split: roughly 60% in Codex and Claude Code shipping customisations, 40% in client rooms understanding what to ship next.

• Customise the agents. Tune prompts, build new agent capabilities, configure workflows, wire up integrations. Codex and Claude Code are your primary IDEs. You ship working code, not specs for someone else to build.
• Own client outcomes end-to-end. From discovery to live deployment, you are the person responsible for whether the agents actually solve the client’s problem. No PM-engineer handoff to hide behind.
• Problem-solve in real time. Client says “the output tone is off for our brand” or “the research agent is missing X data source” — you diagnose, fix, and redeploy, usually within days.
• Hold your own on creative. When a CMO says “this doesn’t feel right,” you can question intelligently — is it the prompt, the input brief, the brand guidelines themselves, or the client’s own confusion? Most engineers reach for the prompt. The good ones diagnose first.
• Feed learnings back to core product. Anything that gets customised 3+ times becomes a platform feature. You decide what graduates.
• Build the playbook. As we scale from 10 to 50 to 100 clients, the customisation patterns you create become the foundation others work from.

WHAT YOU NEED

• Real engineering chops. You can read a codebase, write production code, debug agent failures, and ship to live clients. AI tools are your accelerant, not your crutch.
• Comfort with agents as a system. You understand how LLMs fail, why prompts drift, what context engineering means, when to use tools vs. fine-tuning, why eval harnesses matter. If “MCP,” “tool use,” and “agent harness” feel like jargon, this isn’t the role.
• Client-facing instincts. Comfortable in a room with a CMO, an enterprise IT head, and a junior brand manager — and you can switch register for each in the same meeting. If client calls feel like tax to you, don’t apply.
• Some creative literacy. You don’t need to be a designer. You do need to be able to tell the difference between “this output is technically broken” and “this output is technically fine but creatively wrong” — and chase the right thread.
• Bias toward shipping. A working hack today beats a clean design next quarter.

YOU'LL THRIVE HERE IF

• You’re an engineer who realised products live or die on customisation, not architecture.
• You’ve been frustrated by being kept away from customers.
• You like building with AI tools and want a role where that’s the job, not a side experiment.
• You like marketing as a domain — or you’re willing to fall in love with it.

YOU WON'T THRIVE HERE IF

• You want to optimise systems in a corner with headphones on.
• You think client calls are below your pay grade.
• You think AI is overhyped (we don’t).
• You need a fully scoped ticket queue and weekly sprint rituals.

SOLARSQUARE  ·  ENGINEERING

Staff Engineer, Data Platform

Team: Data Engineering    ·    Level: Staff (Individual Contributor)    ·    Experience: 8+ years      ·    Full-time

Own the data platform that turns every customer and field interaction into a decision SolarSquare can act on.

About SolarSquare :

At SolarSquare we are building the Home-Energy brand of future India. We help homes switch to rooftop solar and move away from traditional coal electricity. We are a full-stack D2C residential solar brand — designing, installing, maintaining (after-sales), and financing solar systems for home-owners across India.

In a few short years we have scaled to become the leading residential solar brand in India. We are obsessed with quality, customer service, and innovating to make it simple for homes to switch to solar. We are looking for leaders to join us in this mission.

Get to know us

• SolarSquare - company website
• Featured by TIME as one of the World’s Top GreenTech Companies of 2025
• SolarSquare raises $53M Series C led by B Capital (Moneycontrol)
• India’s rooftop solar market and SolarSquare’s growth (TechCrunch)

About the role :

As a Staff Engineer on Data Platform, you set the technical direction for how we move, model, and serve data across the entire customer lifecycle — from real-time operational streams off thousands of field devices to the analytical layer our leaders and AI systems depend on. You operate at the scope of the platform: ambiguous problems land on your desk, and you turn them into systems the whole org builds on.

What you’ll own :

• Design and scale the data platform end to end: streaming ingestion, batch pipelines, the analytical warehouse, and a governed self-serve metrics layer.
• Build real-time operational data streams that power field operations and customer-facing experiences with low latency and high reliability.
• Own data quality, lineage, and governance — including PII handling — so teams trust the data and never dump it mindlessly.
• Define a golden metrics layer and the standards, contracts, and tooling that make analytics self-serve across the org.
• Set the bar on craft: review designs, clear data tech debt every sprint, and mentor engineers across pods.

The Tech you’ll work with :

You’ll work across event streaming (Kafka), PostgreSQL as the system of record, a columnar analytical warehouse for OLAP, Python-based pipelines, and Metabase for self-serve BI — with more workloads moving to real-time and columnar storage as we scale. We’re stack-agnostic for the right person; fundamentals matter more than any one tool.

What we’re looking for :

• 8+ years building large-scale data systems in production, with deep ownership of at least one major data platform.
• Strong command of distributed data processing and streaming architectures, plus modern columnar / analytical warehouses.
• Expert SQL and data modeling; fluency in data quality, lineage, and governance.
• Proven ability to turn ambiguous business questions into durable data models and reusable platform abstractions.
• Experience setting technical direction and growing the engineers around you.
• Customer-obsessed and impact-led: you start from the customer’s pain and judge yourself by the metric your work moves, not the tickets you close.
• High agency: you don’t wait to be told — you spot problems, pick them up, and own the outcome through to production.
• Craft over shortcuts: you fix root causes rather than symptoms, clear tech debt as you go, and don’t ship bugs.
• Bias for speed and simplicity: you build once for reuse, automate the mundane, and let AI draft the first pass so your judgment goes where it matters.
• Data-driven: you reach for evidence over assumptions and let results guide the next decision.

Bonus points

• Experience with lakehouse architectures, real-time analytics, or geospatial / IoT-scale data.
• Exposure to semantic layers and self-serve analytics platforms.
• Built data platforms that feed ML or AI systems.

Why you’ll love building here

• Direct ownership of high-impact initiatives with visible customer and business outcomes.
• An AI-native engineering culture with first-class tooling and internal agents.
• A high-agency, low-bureaucracy environment where you debate what’s right and ship.
• A meritocracy where growth and recognition track impact, not tenure.
• Competitive compensation.
• A front-row seat to putting clean energy on millions of Indian rooftops.

Primary Skills

• Observability: ELK (Elasticsearch/Kibana), Prometheus, Grafana, PromQL
• Automation: Java/Vert.x or Python (FastAPI), Shell/Bash, REST/SOAP APIs
• Cloud & Platform: Docker, Kubernetes, Kafka, Redis
• Reliability Engineering: Distributed Systems, Microservices, Event-Driven Architecture, DR & Incident Management
• Stakeholder Management & Cross-functional Collaboration

Secondary Skills

• Agentic AI: LangChain, LangGraph, RAG, MCP
• LLM Integration & AI Frameworks
• Python (FastAPI)

Key Responsibilities

• Build and deploy LLM-powered Agentic AI solutions with tool calling and autonomous workflows.
• Integrate AI capabilities into existing applications using modern AI frameworks.
• Own platform reliability through SLAs, SLOs, error budgets, MTTD/MTTR, and operational governance.
• Enhance observability using ELK, Prometheus, Grafana, and advanced alerting.
• Lead incident response, RCA, disaster recovery, and resiliency initiatives.
• Drive production readiness, automation, platform stability, and infrastructure optimization.

About the role:

Unico Connect is an Al-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Senior Al Engineer for a dedicated client engagement focused on building an Al-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code. The mandatory requirement for this role is hands-on production experience shipping LLMpowered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage. The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy. You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent architecture: Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions. Make and revisit architectural decisions on singleagent vs. multi-agent designs, including planner/executor splits and dedicated buildrepair sub-agents.

Code generation pipeline: Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit. Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies. Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-repair loop: Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation. This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context management: Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval. Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes. Own token budgeting and prompt caching strategy.

Prompt engineering as a discipline: Own the system prompt and per-task prompt variants (new feature, bug fix, styling change). Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites. Version prompts like code with changelogs and rollback capability.

Evaluation and quality measurement: Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant. Define regression gates that block qualitydegrading changes from shipping. Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time. This responsibility is nonnegotiable at this level. 

Model strategy and cost: Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation. Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection. Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and reliability of agent behaviour: Defend against prompt injection from user content and fetched web content. Ensure secrets never appear in generated client code. Define what the agent's tools may and may not do in collaboration with the platform team. Contribute to output moderation and abuse-pattern awareness.

Mentorship and engineering standards: Run code reviews, define engineering conventions for Al work, and raise the engineering bar across the Al team. Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on production ownership of LLM-powered systems with agent architectures (mandatory). Must have personally shipped and operated at least one complex production Al system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost. POCs, internal demos, and tutorialgrade work do not qualify.

5+ years of professional software or Al engineering experience, with at least 3 years focused on LLM applications, Al engineering, or production Al systems. Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python proficiency and service development. Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging. Not notebook-only. 

Depth across LLM APIs and agent systems. Production experience with at least two of OpenAl, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together). Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, Llamalndex Agents) or hand-rolled equivalent. Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, systematic evaluation practice - non-negotiable. Must have built evaluation harnesses that gate production releases, not ad-hoc testing. Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval. Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost discipline for production Al. Track record of measurable cost optimisation on production Al features. Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS working knowledge. Hands-on with EC2, S3, IAM, and Docker. Comfort with CI/CD workflows and deploying Al services.

Awareness of LLM security failure modes. Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to have: experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work; MCP server authoring; open-source Al contributions; published technical writing on LLM systems; multi-modal model experience; fine-tuning exposure (LORA, QLORA, PEFT).

Visionyle is Hiring for UK Based Company- Lead Data Architect 

Role:

· Lead Data Architect Snowflake

Job Location: Mumbai, Pune

Experience: 15-25 yrs

Client: Capita

Job Type: FTE

Job Description: 

· Mandatory Skills:

Data Architecture, Microsoft Azure, Databricks, Snowflake, Azure Synapse Analytics, Data Modelling, Application Integration, Presales.

· Good to Have Skills:

Microsoft Fabric, Data Strategy / Governance, Data Visualisation, Data Science / AI, DevOps / Cloud Infrastructure

· Experience in end-to-end project all aspects of our delivery right from initiating a project from technology side, initiating a project meaning understanding the requirements from stakeholder, designing architecture in it right up to production and production support organization, support, pre-sales, estimations, costing.

Certifications:

Candidates possessing one or more of the following certifications will be highly preferred:

• Databricks Certified Data Engineer Associate or Professional

• Databricks Partner Solution Architect Champion

• SnowPro Advanced: Data Engineer

• SnowPro Advanced: Architect

• Microsoft Azure Certifications in Data Engineering, Artificial Intelligence (AI), or Solution Architecture.

Applicants holding any of the above certifications are encouraged to apply.

Roles & Responsibilities:

· The Lead Data Architect is responsible for providing strategic leadership and technical expertise in data architecture to drive innovation and excellence in solution delivery.

· With a focus in client satisfaction and project success, lead a team of data professionals, providing mentorship, guidance and support to ensure the successful execution of projects

Visionyle is Hiring Lead Data Architect 

Role:

· Lead Data Architect Snowflake

Job Location: Mumbai, Pune

Experience: 15-25 yrs

Client: Capita

Job Type: FTE

Job Description: 

· Mandatory Skills:

• Data Architecture, Microsoft Azure, Databricks, Snowflake, Azure Synapse Analytics, Data Modelling, Application Integration, Presales.

· Good to Have Skills:

• Microsoft Fabric, Data Strategy / Governance, Data Visualisation, Data Science / AI, DevOps / Cloud Infrastructure
• Experience in end-to-end project all aspects of our delivery right from initiating a project from technology side, initiating a project meaning understanding the requirements from stakeholder, designing architecture in it right up to production and production support organization, support, pre-sales, estimations, costing.

Certifications:

Candidates possessing one or more of the following certifications will be highly preferred:

• Databricks Certified Data Engineer Associate or Professional

• Databricks Partner Solution Architect Champion

• SnowPro Advanced: Data Engineer

• SnowPro Advanced: Architect

• Microsoft Azure Certifications in Data Engineering, Artificial Intelligence (AI), or Solution Architecture.

Applicants holding any of the above certifications are encouraged to apply.

Roles & Responsibilities:

• The Lead Data Architect is responsible for providing strategic leadership and technical expertise in data architecture to drive innovation and excellence in solution delivery.
• With a focus in client satisfaction and project success, lead a team of data professionals, providing mentorship, guidance and support to ensure the successful execution of projects

Mandatory Skills:

• Strong hands-on experience in Python
• Experience in Generative AI / LLMs
• Good understanding of FinTech or Banking domain
• Experience with APIs and Microservices
• SQL/Database knowledge
• Cloud platform experience (AWS/Azure/GCP)
• Strong communication and problem-solving skills

Job Title : AI Engineer

Experience : 2+ Years

Location : Mumbai (Onsite)

Employment Type : Full-Time

Reports To : AI Architect

About the Role :

We are looking for an AI Engineer with 2+ years of experience to design, assess, validate, and deploy AI solutions for enterprise clients. This is a hands-on role focused on building scalable, production-ready AI systems aligned with business outcomes.

The ideal candidate should enjoy solving complex problems, working with emerging AI technologies, and translating business needs into practical AI solutions.

Mandatory Skills :

Python, Large Language Models (LLMs), Generative AI, AI Agents/Agentic Workflows, Prompt Engineering, Retrieval-Augmented Generation (RAG), LangChain, OpenAI APIs (or equivalent), Vector Databases, REST APIs, AI Workflow Orchestration, Client-Facing Experience, and Strong Analytical & Problem-Solving Skills.

Key Responsibilities :

• Analyze and improve existing AI workflows, LLM implementations, and AI agents.
• Design AI solutions and agent workflows aligned with business objectives.
• Define and implement AI guardrails, governance practices, and risk controls.
• Build evaluation frameworks to measure accuracy, reliability, latency, and cost efficiency.
• Ensure AI systems are scalable, secure, and production-ready.
• Work closely with stakeholders and communicate technical concepts clearly.

Required Skills & Qualifications :

• 2+ years of experience in AI/ML Engineering, Generative AI, Machine Learning, or related domains.
• Strong analytical thinking and problem-solving skills with a systems-oriented mindset.

Hands-on experience with :

• Large Language Models (LLMs)
• AI Agents and Agentic workflows
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI workflow orchestration

Strong proficiency in :

• Python
• REST APIs
• Data structures and algorithms
• Experience working with:
• LangChain or similar frameworks
• OpenAI APIs or equivalent AI platforms
• Vector databases
• Embedding models

Understanding of :

• AI governance
• Model evaluation techniques
• Responsible AI principles
• Strong written and verbal communication skills.

Preferred Skills :

• Experience in client-facing or consulting environments.
• Exposure to enterprise AI implementations and production deployments.

Experience with :

• Cloud platforms (AWS, Azure, or GCP)
• Docker and containerized deployments
• MLOps practices
• AI monitoring and observability tools
• Exposure to regulated or high-risk industries is a plus.

Educational Qualification :

• Bachelor's degree in Computer Science, Engineering, AI, Data Science, or related field.
• Equivalent practical experience with strong projects and technical expertise may also be considered.

Software Tester – Automation - Arcitech AI

Role Overview

We are seeking a skilled Automation Tester with strong hands-on experience in Python-based UI, API, and WebSocket automation. The role involves close collaboration with developers, project managers, and QA teams to ensure product quality, performance, and reliability. You will also contribute to exploring and implementing AI-driven testing initiatives.

Key Responsibilities

Requirement Analysis and Test Planning

• Participate in client discussions to understand testing and automation needs
• Translate functional and technical requirements into automation-ready test scenarios

Automation Testing and Framework Development

• Develop and maintain automation scripts using Python, Selenium, and Pytest
• Build and enhance scalable automation frameworks for UI, API, and WebSocket testing
• Improve reusability, modularity, and performance of automation scripts

API and WebSocket Testing

• Perform REST API validation using Postman and Swagger
• Develop automated API test suites using Python and Pytest
• Execute WebSocket test scenarios including real-time validations, latency checks, and connection stability

Manual Testing

• Conduct functional, UI, smoke, sanity, and exploratory testing as required
• Validate applications across development, QA, and production environments

Defect Management

• Log, track, and retest defects using tools such as Jira or Zoho Projects
• Ensure high-quality bug reporting with clear reproduction steps and severity classification

Performance Testing

• Conduct load and stress testing using JMeter for APIs and WebSocket-based systems
• Analyze system performance and identify bottlenecks

AI-Driven Testing Initiatives

• Research and experiment with AI tools to enhance automation coverage
• Suggest improvements for regression testing, analytics, and optimization

Collaboration and Reporting

• Participate in daily stand-ups and QA sync meetings
• Communicate risks, blockers, and progress effectively
• Prepare reports on automation execution, defect trends, and performance metrics

Requirements

• Strong proficiency in Python
• Experience with Selenium for UI automation (Python)
• Hands-on experience with Pytest framework
• Experience in API testing using Postman or Swagger
• Exposure to WebSocket testing
• Experience with performance testing using JMeter
• Familiarity with CI/CD tools such as Jenkins
• Working knowledge of Git
• Basic SQL knowledge (preferred)
• Experience in manual and functional testing
• Solid understanding of SDLC, STLC, and QA processes

Soft Skills

• Strong communication and collaboration abilities
• Detail-oriented with strong analytical thinking
• Problem-solving mindset
• Ownership and accountability

Why Join Us

• Growth-oriented environment with modern, automation-focused projects
• Opportunity to work on advanced testing practices, including AI-driven initiatives
• Supportive and collaborative team culture
• Structured work-life balance with weekends off
• Provident Fund and employee benefits
• 
  

Immediate Hiring: GCP DevOps Engineer | Mumbai & Bengaluru (On-site)

OpsTree Global is urgently hiring a GCP DevOps Engineer with 4–9 years of experience for immediate requirements in Mumbai and Bengaluru.

Key Skills

• Google Cloud Platform (GCP)
• Terraform / Infrastructure as Code (IaC)
• Kubernetes & Helm Charts
• CI/CD – Jenkins, GitLab CI, GitHub Actions
• Linux Administration
• Scripting – Python / Go / Java
• 
  

Role Responsibilities

• Build and manage scalable cloud infrastructure on GCP
• Automate deployments and infrastructure provisioning
• Ensure system reliability, monitoring, and performance optimization
• Collaborate with development and operations teams for seamless delivery

📍 Locations: Mumbai & Bengaluru (On-site)

⚡ Immediate Joiners Preferred

💼 Experience: 4–9 Years

We're hiring a Tech Lead to own the backend architecture and engineering culture of a fast-growing HR-Tech platform used by 100+ enterprise clients across India.

This isn't a "manage the team and attend standups" role. You'll be hands-on with architecture decisions, own the deployment environment, and work directly with founders who came from Gallup and IIM Ahmedabad.

The stack is Node.js, Docker, Kafka, and cloud (AWS / Azure / GCP).

The role is right for you if:

- You've led backend teams and still enjoy being close to the code

- You've built or significantly improved a CI/CD pipeline in production

- You can explain a technical trade-off to a business stakeholder without making them feel talked down to

- You want ownership, not just a title.

What you'll be doing:

- Designing and maintaining backend systems built for scale, security, and reliability

- Leading and mentoring a team of backend engineers through sprint cycles and beyond

- Owning cloud infrastructure (AWS / Azure / GCP) and keeping deployments stable and fast

- Improving CI/CD practices and automating what shouldn't require human intervention

- Translating product requirements into technical specs the team can actually execute

- Conducting code reviews that raise quality without slowing people down

- Working directly with founders and business stakeholders — not through layers of management

What we're looking for:

- 5–8 years of software engineering experience, with at least 2 years in a lead or senior role

- Strong backend development skills in Node.js (Python or Java is a bonus)

- Hands-on cloud experience — building and managing infrastructure, not just deploying to it

- Comfort with Docker, Kafka, and Linux environments

- Experience running Agile teams — sprint planning, retrospectives, the works

- Clear communication and the ability to make decisions under ambiguity

- B.Tech / B.E. in Computer Science or Information Technology

Location: Mumbai (on-site) Experience: 5–8 years Start: Immediate

If this sounds like the role you've been looking for, apply below or send a message directly. The process is fast and so is the decision.