Gen AI - Engineer

Key Responsibilities

1. Generative AI Design & Developmenta. Contribute to the design 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.

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. Collaborationa. Participate in code reviews, design discussions, and documentation.

b. Follow best practices in coding standards, testing and DevOpsc. Collaborate with team.

Required Skills

1. Strong hands-on proficiency in Python (Flask, REST, async programming).
2. Practical experience with Generative AI and LLM-based applications.
3. Good understanding of RAG system, embeddings, vector databases.
4. Exposure to Agentic frameworks (LangChain 1.0, LangGraph, ReAct, OpenAI Assistants, or custom agents).
5. Familiarity with AWS Cloud (ECS, S3, API Gateway, IAM, Bedrock).
6. Experience with API development, microservices, containerization etc.
7. Knowledge of CI/CD pipelines, Docker, GitLab/GitHub Actions.

Mandatory Competencies

1. Data Science and Machine Learning - Data Science and Machine Learning - Gen AI
2. Programming Language - Python - Flask
3. Cloud - AWS - AWS S3, S3 glacier, AWS EBS
4. Beh - Communication
5. DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - GitLab,Github, Bitbucket
6. Development Tools and Management - Development Tools and Management - CI/CD
7. Cloud - GCP - Apigee API Management, API Gateway