Lead AI Engineer

We are partnering with a global digital engineering and technology organization to hire a Lead AI Engineer for a brand-new AI engineering initiative in the US. This is a senior, hands‑on technical leadership role combining approximately 50% engineering with 50% architecture, technical direction, and mentorship. You'll join at the very beginning of a new engagement, helping establish the technical foundations for an AI Engineering pod focused on building robust, scalable agentic AI experiences and workflows. This is not a hands-off architecture or people-management position. We're looking for someone who can set technical direction, mentor experienced engineers, make architectural decisions and still spend significant time writing and reviewing production code.

What You’ll Be Doing

• Set the technical direction for an AI Engineering pod and own architecture decisions within your area.
• Spend approximately 50%+ of your time hands‑on, writing and reviewing production code.
• Build backend AI services, LLM orchestration layers, APIs, and frontend integrations.
• Design and develop agentic AI experiences, including multi‑step and multi‑agent workflows.
• Build streaming, responsive, low‑latency AI‑powered user experiences.
• Provide technical leadership and mentorship to a pod of senior software and data engineers.
• Conduct architecture and design reviews and unblock complex engineering challenges.
• Partner closely with Security, Data, Infrastructure, Product, and Engineering teams.
• Collaborate with US‑based product and engineering stakeholders throughout delivery.
• Establish strong engineering standards around observability, SLOs, reliability, security, and scalability.
• Help shape engineering practices for a completely new team and initiative.

What We’re Looking For:

Technical Leadership

You’ll bring 8+ years of software engineering experience, including ownership of complex backend systems from design through production. You should have experience providing technical direction and mentorship to experienced engineers while remaining actively involved in delivery.

Hands‑On AI Engineering

You’ll need recent production experience building with Generative AI, LLMs, and agentic AI systems. Ideally, you’ll have 1‑2+ years working with modern LLM‑era AI platforms and frameworks. Candidates with deeper traditional machine learning experience who have made a clear and recent move into Generative AI will also be considered.

Python 5+ years of advanced Python experience is required, particularly across backend services, APIs, AI integrations, and production systems. Python will be the primary language across the backend and AI environment.

Agentic AI & LLM Orchestration

• LangChain
• LangGraph
• Multi‑step agent workflows
• Multi‑agent orchestration
• Tool use and integrations
• State and context management
• LLM evaluation and observability

Frontend Engineering

You should bring approximately 3‑4+ years of React and TypeScript experience. You do not need to be a dedicated frontend engineer, but you should be comfortable meaningfully contributing to UI‑layer code and reviewing frontend work produced by your team.

Cloud & Platform Engineering

Strong production experience within AWS and modern cloud‑native environments, ideally including: AWS Docker GitHub Actions ArgoCD Terraform or OpenTofu Microservices RESTful APIs Security A strong security mindset is important. You should be comfortable working with: Secure coding practices Authentication and authorization Data governance Production security standards

Nice to Have Additional experience

• MCP (Model Context Protocol)
• LangSmith
• RAGAS or custom AI evaluation frameworks
• Retrieval‑Augmented Generation (RAG)
• Vector databases and enterprise search
• OpenSearch
• Amazon Kendra
• AWS Bedrock
• IAM / CIAM
• TensorFlow or scikit‑learn
• Unstructured or multimodal data, including images and video
• Complex prompt and agent context management using LangGraph State