Job Opportunities API

About the Company   At Future Secure AI, we're building something genuinely new — and we're looking for people bold enough to build it with us. We work at the frontier of AI, tackling big, real-world problems for global enterprises across multiple industries, armed with state-of-the-art technology and a culture that prizes courage, rigor, and relentless curiosity. Our BRAVER values aren't just words on a wall — they describe the kind of people we are and the standard we hold ourselves to every day. Our leadership team is entrepreneurial, experienced, and accessible, with an open-door policy that means you'll never be just a number here. We invest seriously in your growth because we know our success depends on yours. If you're ready to work alongside some of the brightest minds in the industry, push into uncharted territory, and do work that genuinely matters, Future Secure AI is the place for you. About the Role   Future Secure AI is looking for a Senior Product Manager to own the AI layer of our enterprise agentic AI platform. You will be responsible for the evaluation of capability, trust and governance posture, observability and explainability primitives, and the agent-design patterns that engineering teams use to build AI Co-Workers for enterprise customers. Your goal is to make the AI layer reliable, auditable, and adoptable in regulated environments, so every AI Co-Worker built on the platform inherits enterprise-grade quality. You will operate as a peer of engineering and AI/ML leadership, with direct impact on whether AI Co-Workers reach scale in regulated industries.   Responsibilities   Own the platform’s evaluation capability and the quality bar that every AI Co-Worker must meet before it ships, spanning offline, online, regression, and rubric-based dimensions   Advance the platform’s AI governance posture covering trust, explainability, observability, and audit to meet the bar set by enterprise compliance reviews across regulated industries   Own the platform’s agent-design primitives (planning, tool use, memory, retries, circuit breakers, human-in-loop checkpoints) and the patterns that guide engineering teams to use them well   Own the model and prompt lifecycle: how versions are introduced, evaluated, promoted, and retired, with change management appropriate to enterprise customers   Drive discovery through interviews with platform engineers, production behavior analysis, frontier research, and enterprise customer conversations, and prototype eval and guardrail primitives before committing engineering capacity   Partner closely with engineering leadership to ensure the platform delivers a reliable, intuitive experience for teams building agentic AI Co-Workers   Own value risk and viability risk: ensure engineering teams adopt your primitives as the fastest path to a reliable AI Co-Worker, and that governance, observability, and audit features satisfy enterprise compliance requirements   Minimum Qualifications   Demonstrated experience building or owning an evaluation suite for an AI feature in production, including offline benchmarks, online evals, regression evals, and rubric-based grading   Nuanced understanding of foundation models, agent architectures, and AI evaluation, with the ability to simplify that complexity for executive, business, and regulated-customer audiences   Direct experience with non-determinism in AI systems; able to write acceptance criteria that hold up under flaky model behavior and set quality SLAs that do not break the team   Experience shipping or working closely on a production agent system, with informed opinions on planning loops, tool use, memory, retries, guardrails, and when an agent is the wrong abstraction   Familiarity with NIST AI RMF and the EU AI