Location: | Experience: 5+ years Role Overview We’re hiring an AI Engineer to design, build, and productionize GenAI and agentic systems (RAG, tool-using agents, workflow/graph-based orchestration) on one or more hyperscalers (Azure, AWS, GCP). You’ll develop the full lifecycle—data/feature/RAG pipeline design, model selection/finetuning, safety/guardrails, evaluation/observability, and MLOps deployment. Key Responsibilities • Build GenAI/agentic systems (chat copilots, workflow/graph agents, tool use, memory) • Implement chunking, hybrid search, vector stores, re-ranking, feedback loops, and continuous data quality/eval. • Select/integrate/finetune LLMs & multimodal models. • Apply prompt-engineering techniques to specific use cases and types • Experience working on solutions based on LLM, NLP, DL (Deep Learning), ML (Machine Learning), object detection / classification etc. • Should have good understanding of DevOps • Should have good understanding of LLM evaluation • Should have deployed min of 2 models in production (MLOps) • Should have understanding of guardrails, policy filters, PII redaction, runtime monitors and agent observability. • Unit testing of GenAI Solutions built and documentation of results. • Collaborate with clients/Stakeholders from multiple Geographies. • Stay informed about the latest advancements in Gen AI, machine learning, and AI technologies to optimize our technical stack. Qualifications • Bachelor’s/Master’s Degree or equivalent. • 5+ years in ML engineering, around 1+ years of hands-on with LLMs/GenAI and agentic frameworks. • Experience in shipping production AI systems on at least one hyperscaler (Azure/AWS/GCP). • Experience delivering end-to-end GenAI based solutions. Required Skills • Strong Python experience to build multiple AI-ML/ GenAI Solutions. • Should have experience working on Agent orchestration with leading frameworks like LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen. • Strong experience working on SQL Query, Vector DB like Pinecone, Qdrant, Fiaas • Should have experience working on hybrid search and re-rankers • Should have experience on evaluation & observability LangSmith/ human-in-the-loop workflows. • Strong experience in using any one of the leading Hyperscaler services from Azure/AWS/GCP • Experience working on NLP, CV, Deep Learning Algorithms • Should have working experience with Open-Source Models • Experience on UI/UX will be added advantage. \#GenAINTT ________________________________________ RESUME SELECTION Guidelines: • Delivered at least 2 GenAI/Agentic AI solutions for clients • Extensive experience of minimum 5+ years on Python • Delivered 3–5 successful client POCs/MVPs \#GenAINTT