About this role

Set technical direction: Own architecture for our most complex GenAI and agentic systems end-to-end, and set the standards — evaluation, observability, responsible AI — that the practice builds to.
Build at the frontier, hands-on: Stay in the code where it matters most — foundation-model and embedding fine-tuning, novel agentic workflows, advanced RAG and semantic search — using Python on Google Cloud (Vertex AI), LangChain/LlamaIndex, and vector search (Vertex AI Vector Search, Pinecone, pgvector).
Engineer for production: Design for latency, reliability, cost, and scale from day one; apply MLOps discipline so systems are served efficiently, monitored, and continuously improved — and actually reach production, where most AI work stalls.
Lead multi-step reasoning at scale: Architect and operate agentic workflows that automate complex reasoning reliably, with the design and verification discipline that keeps multi-agent systems from cascading into failure.
Advise clients and shape deals: Work directly with client leadership to understand strategy, propose state-of-the-art approaches, and shape solutions in pre-sales — the technical authority in the room.
Multiply the team: Elevate senior and mid-level engineers through architecture reviews, mentorship, and setting a high, teachable bar for AI-augmented engineering.

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
10+ years in software / AI / ML engineering, with a substantial track record of AI systems delivered to production at scale.
Demonstrated technical leadership — owning architecture and setting direction across engagements or teams, not just individual deliverables.
Proven track record of deploying GenAI and/or agentic products to production environments.
Experience with classic machine learning (neural nets, training, tuning) strongly preferred; foundation-model or novel-model work a distinct plus.
Strong data engineering and SQL knowledge.
Senior client-facing experience — translating technical complexity into business value for executive stakeholders.

Principal AI Engineer

Key skills