Job description

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 Act, and the ability to map enterprise compliance requirements across banking, insurance, and healthcare to platform primitives Experience living through an AI incident, root-causing it, and shipping the fix into the platform so downstream teams inherit the improvement Preferred Qualifications Background as an AI or ML PM at an enterprise AI platform, an AI tooling vendor, or a model lab Experience in a product role at a regulated-industry AI team that has shipped to production Familiarity with RAG patterns, eval tooling, agent frameworks, and the broader AI tools landscape ML-leaning PM background at a company that has matured past the prototype phase Why Join Us? A high-performance culture State-of-the-art technology Experience world-class leadership Scale of impact and purpose A competitive salary and a huge growth trajectory Work with the best in the industry Flexible work environment Diversity and creativity Disclaimer : We do not wish to be contacted by recruitment agencies. Our hiring process is managed in-house and the best way for candidates to express interest is by applying with your resume through our company website. Future Secure AI Privacy Policy At Future Secure AI, we are committed to protecting your privacy and adhering to the principles of the General Data Protection Regulation (GDPR) and the Australian Privacy Principles (APPs) under the Privacy Act 1988 (Cth). Our Privacy Policy outlines how we collect, use, share, and protect your personal data when you visit our website at www.futuresecure.ai (the "Website") and use our services.

Requirements

Must-haves

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
Partner closely with engineering leadership to ensure the platform delivers a reliable, intuitive experience for teams building agentic AI Co-Workers
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 Act, and the ability to map enterprise compliance requirements across banking, insurance, and healthcare to platform primitives
Experience living through an AI incident, root-causing it, and shipping the fix into the platform so downstream teams inherit the improvement

Nice-to-haves

Background as an AI or ML PM at an enterprise AI platform, an AI tooling vendor, or a model lab
Experience in a product role at a regulated-industry AI team that has shipped to production
Familiarity with RAG patterns, eval tooling, agent frameworks, and the broader AI tools landscape
ML-leaning PM background at a company that has matured past the prototype phase
Why Join Us?
A high-performance culture
State-of-the-art technology
Experience world-class leadership
Scale of impact and purpose
A competitive salary and a huge growth trajectory
Work with the best in the industry
Flexible work environment

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiml

Platform: greenhouse
Effort: quick