Full stack developer
Capgemini Engineering
Gurgaon, Haryana, India2h agovia LinkedIn
This job at a glance
- Who can apply
- Freshers
- Must know
- PythonFastAPIMicroservicesLLMsDockerKubernetes
- Work
- On-site in Gurgaon
- Pay
- Not stated by the employer.
- Skill demand
- Python35%LLMs15%FastAPI10%Microservices10%of 104 similar fresher jobs posted in India this week
- Listed
- 4 Nov 2026 · still open
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About the Role
Capgemini Engineering is seeking a Full stack developer.
Key Responsibilities
- Develop Back-End solutions using Python, FastAPI, and Microservices.
- Work with GenAI technologies, including LLMs, RAG, and Agentic AI.
- Utilize Agent Frameworks such as LangGraph, LangChain, CrewAI, and Semantic Kernel.
- Implement solutions on AI Platforms like MCP, HITL, and Function Calling.
- Deploy and manage applications on Cloud platforms including AWS, Docker, and Kubernetes.
- Implement CI/CD pipelines.
- Build Integration solutions using APIs and Event-Driven Architecture.
- Implement Monitoring strategies with Observability, Telemetry, and LangSmith.
- Focus on Enterprise AI aspects, including LLMOps, AI Governance, and Automation.
Requirements & Tech Stack
- Back-End: Python, FastAPI, Microservices
- GenAI: LLMs, RAG, Agentic AI
- Agent Frameworks: LangGraph, LangChain, CrewAI, Semantic Kernel
- AI Platform: MCP, HITL, Function Calling
- Cloud: AWS, Docker, Kubernetes, CI/CD
- Integration: APIs, Event-Driven Architecture
- Monitoring: Observability, Telemetry, LangSmith
- Enterprise AI: LLMOps, AI Governance, Automation
Qualifications
- Experience with Python, FastAPI, Microservices.
- Familiarity with GenAI concepts (LLMs, RAG, Agentic AI).
- Proficiency in Agent Frameworks (LangGraph, LangChain, CrewAI, Semantic Kernel).
- Knowledge of AI Platforms (MCP, HITL, Function Calling).
- Experience with Cloud technologies (AWS, Docker, Kubernetes, CI/CD).
- Understanding of Integration patterns (APIs, Event-Driven Architecture).
- Skills in Monitoring tools and concepts (Observability, Telemetry, LangSmith).
- Experience with Enterprise AI practices (LLMOps, AI Governance, Automation).