AI Engineering lead

Role & responsibilities

1. Architect and maintain agentic pipelines (LangGraph, CrewAI, AutoGen).

2. Implement RAG, prompt engineering, context/memory/state management.

3. Develop, fine-tune, and evaluate LLM models (Bedrock, OpenAI, Anthropic).

4. Prototype classical ML models (forecasting, clustering, scoring) when required for hybrid AI systems.

5. Deploy via SageMaker / ECS / Lambda with observability hooks

6. Implement guardrails, evaluation metrics, and cost/performance optimization.

7. Advise BA team on model selection, explainability, and feasibility.

8. Python backend devloper having understanding of design patterns .

Preferred candidate profile

1. LangGraph / CrewAI / AutoGen / LangChain / LlamaIndex

2. Python (async), FastAPI, MLflow, PyTorch / Scikit-learn

3. LLM fine-tuning (LoRA, PEFT, embeddings, prompt tuning)

4. Vector DBs: FAISS, Pinecone, Chroma

5. AWS: Bedrock, SageMaker, Step Functions, ECR

6. Statistical ML, feature engineering, XAI (SHAP/LIME)