Senior Frontier AI Deployment Engineer

What you will do

• Lead discovery with business, product, data, security, and engineering stakeholders; convert ambiguous needs into clear use cases, requirements, acceptance criteria, risks, and delivery plans.
• Act as the connective layer among teams in India, Europe, and North American Central and Pacific time zones, creating crisp decisions, handoffs, documentation, and follow-through.
• Shape solution designs for retrieval-augmented generation (RAG), AI agents, tool use, orchestration, evaluation, guardrails, observability, and human-in-the-loop workflows.
• Guide prototypes and production implementations, making pragmatic tradeoffs across user value, model quality, latency, cost, security, reliability, and maintainability.
• Partner with engineers and architects on interfaces, data flows, integrations, deployment patterns, and operational readiness; contribute code or technical artifacts when it accelerates delivery.
• Own stakeholder-facing demos and the supporting demo sites and environments, including setup, access, content and data readiness, reliability, presentation quality, and ongoing maintenance; lead stakeholder updates and technical workshops.
• Define meaningful success measures and evaluation approaches for AI quality, safety, adoption, and business impact.
• Stay current on rapidly changing AI capabilities and translate new developments into practical recommendations rather than technology for its own sake.
• Required qualifications
• 6+ years of experience in software, data, ML/AI, solutions engineering, technical product delivery, or a closely related field.
• Demonstrated senior-level ownership of ambiguous, cross-functional initiatives, including driving decisions and delivery across multiple phases rather than contributing only to isolated technical tasks.
• Demonstrated delivery experience with at least one generative AI system, such as RAG, AI agents, copilots, semantic search, or LLM-enabled workflow automation. Candidates need not have built every component alone, but must clearly explain their contribution and the system’s end-to-end behavior.
• Excellent written, verbal, and visual communication, including the ability to explain technical choices to nontechnical stakeholders and business context to engineers.