Generative AI Engineer

Job Location : Hyderabad / Bangalore / Chennai / Kolkata / Noida/ Gurgaon / Pune / Indore / Mumbai

Experience: 4 to 18 years

Role Overview:
You will be responsible for the hands-on development coding and deployment of AI-powered features. Your focus is on writing clean efficient code to integrate LLMs into our existing tech stack building robust data pipelines for RAG and ensuring the reliability of model outputs through rigorous testing and optimization.

Key Responsibilities

• Application Implementation: Code and integrate LLM APIs (OpenAI Anthropic etc.) or local models into backend services usingPython FastAPI etc.

• MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript)to expose internal databases APIs and file systems to AI agents.

• RAG Implementation: Build and maintain the plumbing for Retrieval-Augmented Generationspecifically coding the data ingestion scripts text chunking logic and metadata filtering.

• Vector DB Management: Perform day-to-day operations on vector databases (Pinecone Milvus etc.) including indexing querying and optimizing search retrieval.

• Prompt Programming: Develop version-control and refine complex prompt templates (using Jinja2 or similar) to ensure consistent structured outputs (JSON/YAML).

• Agent Development: Implement multi-step workflows usingLangChain LangGraph CrewAI etc. focusing on tool-calling logic and error handling.

• Evaluation & Testing: Build automated test suites to detect hallucinations and measure accuracy using frameworks.

• Performance Tuning: Implement caching layers and streaming responses to reduce latency and improve the end-user experience; Token optimization.

• Data Pre-processing: Clean and tokenize datasets for model fine-tuning or high-quality context retrieval.

Technical Skills (The Execution Stack)

• Language: AdvancedPython(Asyncio Pydantic) and optionalTypeScript/(for full-stack integration).

• AI Frameworks: Hands-on experience with any ofLangChainLlamaIndex andHugging FaceTransformers. RAG and Vector search concepts.

• Data Handling: Proficiency inSQLand handling unstructured data formats (PDFs Markdown JSON).

• Deployment: Practical experience withDocker GitHub Actions (CI/CD) and experience with OpenTelemetry LangSmithWeights & Biasesetc. Understanding of evaluation/guardrails.

• MCP/API Proficiency: Deep understanding of RESTful APIs Streaming HTTP MCP server vs client JSONRPC