Staff AI Platform Engineer

About the OpportunityOscar Faye is partnering with a $30B+ alternative asset manager to hire a Staff AI Platform Engineer as one of the first members of a brand new AI team. The firm operates across five distinct verticals — digital assets, reinsurance, alternative lending, energy, and fine art — and has made an explicit, top-down commitment to becoming an AI-first organization. The cloud foundation is already in place, early primitives are already shipping, and engineers across the firm are already building on them. This is not exploration. This is execution.The RoleYou will architect and build the reusable backend platform components and agent infrastructure that every AI workload across the firm depends on. You report directly to the Head of AI and operate with genuine startup ownership inside a well-capitalized firm. This is a hands-on individual contributor role. You are not managing. You are building the foundation everything else runs on top of.What You'll DoArchitect and build the agent platform — runtime, tool integrations, evaluation frameworks, and guardrails that AI workloads across five business verticals depend onIdentify where multiple teams are solving the same underlying problem and build the shared component once, well, so capability compounds across the firm rather than fragmentsExtend the AI-native cloud stack with real ownership over what gets adopted and whyPartner directly with quants, portfolio managers, operations, and legal to translate what they need into durable platform primitives they can use without your helpSet the engineering standard for how the firm adopts emerging AI technology safely — prompt injection, data exfiltration, permissioning, and the discipline that unproven tools requireWhat We're Looking For6+ years of backend engineering, primarily in PythonProven hands-on IC who has built platform or backend systems end-to-end — shared primitives, internal developer platforms, or distributed infrastructure other teams depend onRange to reach for a compiled language when the problem calls for it (Rust, Go, or Java — recency does not matter)Experience with or genuine interest in agent systems, LLM tooling, or internal AI developer platformsComfort with ambiguity — you can self-organize open-ended mandates into shipped workStartup operating mode, whether or not you came from a startupWhat We're Not Looking ForEngineers who need heavily scoped tickets or defined roadmaps to operateApplication-layer LLM engineers only — chatbots, RAG apps, text-to-SQL with no platform layer underneathPure managers with no hands-on IC work in the last three yearsEnterprise or Solutions Architects without production builder track recordsCandidates with surface-level AI exposure who have not shipped production systemsWhy This Role Stands OutOne of the first hires on a net-new AI team — genuine greenfield architectural ownership from day oneProprietary data across five verticals most engineers never touchDirect line to the Head of AI and CTO — no layers, no political overheadCompetitive compensation structure with long-term upside built in — and a retention rate that speaks for itself