Gen AI developer

Job highlights

• Practical experience with LLM applications,prompt engineering,and RAG.
• Collaborate with architects,QA,and UI developers in an Agile delivery model. . Must-Have Skills . Strong Python (production-grade backend development). Hands-on AWS experience (Bedrock,Lambda,ECS,S3,IAM,API Gateway). .

Description

Experience: 4 to 7 years overall, with hands-on Python and AWS

Role Summary

The GenAI Developer builds and maintains backend services and APIs that power GenAI use cases on AWS. The role covers the full application lifecycle: developing Python services, integrating LLMs and vector search, implementing RAG workflows, and deploying secure, production-ready solutions. The developer works with solution architects and UI teams so that GenAI capabilities are reusable and easy to consume across use cases.

Key Responsibilities

• Design, develop, and deploy Python-based backend services and REST APIs (FastAPI) that expose GenAI capabilities.
• Build RAG pipelines end to end: data preparation, chunking, embedding generation, indexing, retrieval optimization, and response orchestration.
• Integrate LLMs through AWS Bedrock and related services, applying guardrails, prompt management, and responsible AI controls.
• Develop use case solutions that consume GenAI capability services and support UI integration of LLM responses.
• Deploy and run applications on AWS (Lambda, ECS, API Gateway, S3) with CI/CD, monitoring, and logging.
• Work with relational and vector data stores (PostgreSQL/MySQL on RDS, vector databases).
• Write unit and integration tests, review code, and follow secure coding and documentation standards.
• Collaborate with architects, QA, and UI developers in an Agile delivery model.

Must-Have Skills

• Strong Python (production-grade backend development)
• Hands-on AWS experience (Bedrock, Lambda, ECS, S3, IAM, API Gateway)
• Experience building and consuming REST APIs (FastAPI or similar)
• Practical experience with LLM applications, prompt engineering, and RAG
• Working knowledge of SQL databases and vector search

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