GenAI Prompt Engineer/ Data Engineer

GenAI Prompt Engineer Engagement: Contract-to-Hire (36 months). You will be employed and payrolled by us for the contract period, with strong potential to convert to a permanent role with the client or their enterprise partner. Location: Bangalore (on-site / hybrid - details shared at interview) Experience: 58 years About The Role We're hiring a GenAI specialist to join an innovation POD at a leading global CPG, FMCG enterprise, delivered in partnership with a global technology & IT services firm. You'll design, build, and optimize GenAI and Agentic AI solutions for real business use cases across Supply Chain, Procurement, and adjacent domains - moving ideas from prototype to measurable business impact. This is a hands-on, client-facing role for someone who blends prompt, LLM engineering, data pipeline work, and applied ML judgment. Key Responsibilities Design and develop GenAI, Agentic AI solutions and workflowsBuild and optimize prompts, chains, and agents using modern LLM frameworksDevelop data pipelines and perform data analysis to support AI use casesBenchmark and evaluate AI models to select the best fit for each use caseBuild autonomous, semi-autonomous agents for business process automationCollaborate with full-stack developers to integrate AI into applicationsStay current on GenAI, Agentic AI advances and bring new ideas to the PODPresent solutions and their business impact to client stakeholders Must-Have Skills58 years building AI, ML or GenAI applications from an ML Engineering, AI Engineering, or applied Data Science background. Comfortable across the stack prompt, LLM engineering, data pipelines, and applied ML judgment rather than pure research or pure analytics.Hands-on experience building and deploying on Microsoft Azure (required) this is a core requirement, not a nice-to-haveStrong hands-on experience with LLMs (GPT, Claude, open-source models)Proficiency in prompt engineering and LLM app frameworks (LangChain, LlamaIndex, or similar)Experience building Agentic AI workflows (multi-agent systems, tool-use, autonomous agents)Strong Python skillsSolid grasp of data analysis, NLP, and ML fundamentalsGood communication skills for client-facing work Good to HaveAzure AI Services and Azure OpenAIRAG architectures and vector databasesMLOps practices and model deployment pipelinesPrior exposure to CPG, FMCG or manufacturing domain use cases Why This RoleDirect exposure to a marquee global brand's AI innovation charterClear path from contract to permanent conversion for strong performersWork on production GenAI, not just POCs - real business impact across Supply Chain and Procurement .