Generative AI Engineer

Generative AI Engineer

Location: Mumbai

Notice Period : Immediate to 30 Days

Experience: 3-6 years

Key Responsibilities

• Design and develop LLM-powered applications using models such as OpenAI, Claude, Mistral, and other foundation models.
• Build RAG pipelines using vector databases such as Pinecone, FAISS, pgvector, ChromaDB, Qdrant, Milvus, or Weaviate.
• Develop AI applications using LangChain, LlamaIndex, and related GenAI frameworks.
• Build AI agents and multimodal AI solutions involving text, audio, and images.
• Design and optimize prompt templates, chains, agents, and AI workflows.
• Benchmark commercial and open-source LLMs based on accuracy, performance, and cost.
• Evaluate and implement fine-tuning approaches such as PEFT and LoRA where applicable.
• Deploy GenAI solutions on AWS, GCP, or Azure using services such as Bedrock, SageMaker, or Vertex AI.
• Develop scalable APIs and microservices using FastAPI/Flask.
• Implement MLOps practices including CI/CD, model monitoring, drift detection, canary releases, and retraining.
• Ensure performance, security, observability, responsible AI, and compliance of GenAI applications.
• Collaborate with Solution Architects, DevOps teams, Data Scientists, and customers to deliver PoCs and enterprise-grade solutions.
• Document technical frameworks, best practices, risks, and learnings.

Required Skills

• 3+ years of experience in NLP/ML/AI, with at least 3 years of hands-on GenAI experience.
• Strong programming skills in Python.
• Hands-on experience with Generative AI, LLMs, RAG, embeddings, and prompt engineering.
• Experience with LangChain and/or LlamaIndex.
• Strong knowledge of PyTorch and Hugging Face.
• Experience working with LLM APIs such as OpenAI, Anthropic, or Hugging Face.
• Hands-on experience with vector databases such as Pinecone, FAISS, pgvector, Qdrant, Milvus, or Weaviate.
• Experience with at least one cloud platform: AWS, GCP, or Azure.
• Knowledge of transformer architectures and embedding techniques.
• Experience developing APIs using FastAPI or Flask.
• Good understanding of MLOps, CI/CD, Docker, security, and model monitoring.
• Strong communication and stakeholder management skills.