Lead / Manager - AI Engineering

Overview

Hands-on Lead/Manager for GenAI and Agentic AI Engineering, responsible for designing and delivering enterprise-grade AI/ML solutions and ensuring they are measurably effective and safe.

What you'll do

• Translate business needs into testable GenAI and agentic engineering solutions with measurable success criteria.
• Design and implement end-to-end AI/ML systems from data readiness through agentic solution deployment.
• Build and validate GenAI/agentic systems, defining what “good” means and setting release gates.
• Develop evaluation strategy with metrics, fairness/bias considerations, and ground-truth creation.
• Run structured prompt/model experiments and recommend improvements grounded in evidence.
• Design scalable and secure agentic AI architectures following data engineering, MLOps, and LLMOps best practices.
• Provide engineering-ready handoff including prompt/versioning approach, RAG configuration, evaluation harness, and go/no-go gates.

What you'll need

• 5-10 years of overall AI/ML experience.
• At least 2-3 years of experience with Generative AI solutions.
• Deep expertise in LLM, Azure AI, Snowflake, and Machine Learning ecosystems.
• Strong background in evaluation design, metrics, and dataset curation for LLM systems.
• Proficiency in Python and major ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• Experience in LLM fine-tuning and RAG context engineering.
• Experience with Agentic AI SDLC working with GenAI on Azure, AWS, or Snowflake.