AI Platform Engineer

Oscar 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.

You 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.

• Architect and build the agent platform — runtime, tool integrations, evaluation frameworks, and guardrails that AI workloads across five business verticals depend on
• Identify where multiple teams are solving the same underlying problem and build the shared component once, well, so capability compounds across the firm rather than fragments
• Extend the AI‑native cloud stack with real ownership over what gets adopted and why
• Partner directly with quants, portfolio managers, operations, and legal to translate what they need into durable platform primitives they can use without your help
• Set the engineering standard for how the firm adopts emerging AI technology safely — prompt injection, data exfiltration, permissioning, and the discipline that unproven tools require

• 6+ years of backend engineering, primarily in Python
• Proven hands‑on IC who has built platform or backend systems end‑to‑end — shared primitives, internal developer platforms, or distributed infrastructure other teams depend on
• Range 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 platforms
• Comfort with ambiguity — you can self‑organize open‑ended mandates into shipped work
• Startup operating mode, whether or not you came from a startup

• Engineers who need heavily scoped tickets or defined roadmaps to operate
• Application‑layer LLM engineers only — chatbots, RAG apps, text‑to‑SQL with no platform layer underneath
• Pure managers with no hands‑on IC work in the last three years
• Enterprise or Solutions Architects without production builder track records
• Candidates with surface‑level AI exposure who have not shipped production systems

• One of the first hires on a net‑new AI team — genuine greenfield architectural ownership from day one
• Proprietary data across five verticals most engineers never touch
• Direct line to the Head of AI and CTO — no layers, no political overhead
• Competitive compensation structure with long‑term upside built in — and a retention rate that speaks for itself