Mid level GenAI Engineers

• 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 & multimodalmodels
• 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

• 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
• Strong Python experience to build multiple AI-ML/ GenAI Solutions
• 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
• Experience working on hybrid search and re-rankers
• 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
• Working experience with Open-Source Models

Experience on UI/UX will be added advantage