Lead AI Engineer – GenAI & AI Platform
Summary
Lead AI Engineer (hired via TEKsystems for a global retail organization) to lead a team of AI/ML engineers, own the architecture and delivery of production-grade LLM, RAG and agentic AI solutions, and drive scalability and reliability of the enterprise AI platform. Core stack: Python, FastAPI, LangGraph/LangChain, Azure OpenAI, Databricks, Kubernetes.
About the Role
We are hiring a Lead AI Engineer to join a global retail organization undergoing a major AI transformation across multiple markets .
There are two leadership opportunities within the team, covering AI/LLM Engineering and ML/AI Platform Engineering. Depending on your background, you may focus on designing Agentic AI solutions or leading the productionization, scalability, and reliability of enterprise AI platforms.
Key Responsibilities
Lead and provide technical direction to a team of AI/ML Engineers
Own the architecture and delivery of production-grade AI solutions
Design and evolve LLM, RAG, Agentic AI, and multi-agent architectures
Drive productionization, scalability, reliability, and performance of AI platforms
Establish best practices around monitoring, evaluation, testing, and AI governance
Review technical designs and mentor engineers on complex implementation decisions
Lead technical discussions and workshops with business and technology stakeholders
Shape the future direction for AI Transformation and roadmap of the AI platform
What We're Looking For
7+ years of Software, Machine Learning, or AI Engineering experience.
Strong English communication, with the ability to explain architecture, trade-offs, risks, and recommendations to both technical and business stakeholders.
Proven experience building and deploying AI applications into production.
Strong Python and backend engineering capability.
Experience with LLMs, RAG, LangGraph/LangChain, AI Agents, and tool calling.
Strong understanding of APIs, distributed systems, SQL, data platforms, and cloud environments.
Experience with AI/LLM observability, monitoring, evaluation, and production support.
Strong system design and architecture capability.
Proactive and able to work independently with strong technical ownership.
Relevant Technologies
Python, FastAPI, LangGraph, LangChain, Azure OpenAI, RAG, Azure AI Search, Databricks, PostgreSQL, Redis, Docker, Kubernetes, CI/CD, Langfuse, Grafana