Gen AI - EngineerKey Responsibilities
1. Generative AI Developmenta. Contribute in coding and implementation of GenAI-powered applications.
b. Translate functional requirements into efficient Python services.
c. Work with LLM orchestration frameworks (LangChain 1.0, LangGraph, OpenAI tools, custom agents).
d. Participate in PoCs and exploratory work for new GenAI capabilities.
2. Python & Clouda. Build and enhance RAG pipelines using embeddings, vector databases, and chunking strategies.b. Implement basic Agentic workflows under guidance from senior team members. (wherever applicable)
c. Work with vector search systems (PGVector, FAISS, etc.).
d. Implement indexing, metadata tagging, and retrieval optimizations.
e. Exposure to MCP / tool-integration frameworks is an added advantage.
3. Softskills
a. Participate in code reviews, design discussions, and documentation.
b. Follow best practices in coding standards, testing and DevOpsc. Collaborate with team.
Required Skills
hands-on proficiency in Python (Flask, REST, async programming). Practical experience with Generative AI and LLM-based applications. (6 to 12 months)
Good understanding of RAG system, embeddings, vector databases. Usage of Bedrock models through AWS Exposure to Agentic frameworks (LangChain 1.0, LangGraph, ReAct, OpenAI Assistants, or custom agents).
Familiarity with AWS/Azure/GCP Cloud (ECS, S3, API Gateway, IAM, Bedrock). Experience with API development, microservices, containerization, CDK etc. Handson Knowledge Docker, GitHub Actions and policies.

Keyskills: ai api development api gateway react bitbucket 33072 microservices docker analytics automation data science iam gcp devops xml programming azure s3 rest python github llm machine learning ai engineer gitlab flask aws