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.

Work arrangement
No