Senior Consultant

We are seeking Data Scientists/Data Engineers/Generative AI Engineers with strong expertise in LLMs and LLM modelling.
Key Responsibilities: Build GenAI applications using LLMs (OpenAI, bedrock, huggingface etc) Develop RAG pipelines: chunking, embeddings, retrieval optimization,rerankers Implement prompt engineering, evaluation, and guardrails Fine-tune and optimize open-source models (LoRA/PEFT) Design APIs using FastAPI/Flask and integrate with microservices Work with vector databases (Weaviate, Pinecone, Qdrant) Deploy AI workloads on cloud (AWS/Azure/GCP) Monitor model quality, hallucination rates, and performance metrics Required Skills: Strong Python development background Hands-on experience with: LLM APIs: OpenAI, Azure OpenAI, Anthropic, Google Gemini, Groq Open-source models: Llama, Mistral, Mixtral, Falcon, Gemma Fine-tuning frameworks: Hugging Face, PEFT, LoRA Vector DBs: Weaviate, Pinecone, Qdrant, etc RAG pipelines: LangChain, LlamaIndex, Haystack (or custom) Embedding models, chunking techniques, search tuning FastAPI / Flask backend development Cloud: AWS S3, EC2, Lambda, Bedrock (added advantage) Good to Have: Experience with multi-agent frameworks (CrewAI, LangGraph, Autogen). Knowledge of model quantization, GPU optimization, and inference acceleration. Familiarity with DevOps tools (GitHub Actions, Terraform, Docker, Helm). Exposure to security compliance (PII masking, policy enforcement, RBAC). Basic understanding of front-end (React) helpful but optional.