Senior Artificial Intelligence Engineer - LLM/Generative AI

Role : Senior Ai EngineerTotal Experience : 9 Y+Location : PuneNotice : 0-15 daysWe're looking for a hands-on Gen AI pioneer who can architect, code, and mentor. This is a "player-coach" role where you'll be building foundational systems while guiding your team. You will partner daily with product and engineering leadership to transform business goals into cutting-edge, shippable LLM-powered solutions.Key Responsibilities :- Architect & Build RAG Systems: Design, develop, and deploy sophisticated Retrieval-Augmented Generation (RAG) systems to power our next-generation search and discovery experience.- Develop & Fine-Tune LLMs: Lead the development of advanced generative models for nuanced tasks like automated content creation, summarization, and metadata enrichment.- Own the Gen AI Stack: Select, provision, and optimize our stack, leveraging managed services like Azure OpenAI or AWS Bedrock, or self-hosting models on GPU infrastructure. You will establish best practices for repo structure, CI/CD, and model/prompt versioning.- Implement LLMOps: Embed robust observability using tools like OpenTelemetry and Prometheus. This includes tracking standard metrics (latency, cost, accuracy) and specialized monitoring for hallucination, toxicity, and data drift.- Lead & Mentor: Hire, coach, and develop ML talent. Set the standard for high-quality code, rigorous experimentation, and rapid iteration within the Gen AI domain.Must-Have Skills :- Production LLM Experience: 5+ years in Python with demonstrable success in productionizing LLM applications using modern frameworks like DSPY, LangChain, LlamaIndex, or Hugging Face Transformers.- RAG Expertise: Deep, practical knowledge of RAG architecture, including advanced prompt engineering, chunking strategies, and proficiency with vector databases (e.g., Pinecone, Weaviate, Milvus).- Cloud Proficiency: Expertise with managed LLM services (Azure OpenAI Service or AWS Bedrock). Strong foundational cloud skills in either Azure or AWS for compute orchestration (AKS/EKS), serverless functions, and storage.- MLOps Acumen: Solid experience with Docker, CI/CD pipelines (e.g., GitHub Actions, Argo), and model registries.- Leadership & Communication: Proven ability to lead small, highly technical teams and clearly communicate complex concepts to stakeholders. (ref:hirist.tech)