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 architecture and deployment surface of our enterprise agentic AI platform — the layer where the platform meets each customer’s real cloud, identity, security, and operational environment. You will lead architecture conversations with enterprise customers, set up the supported deployment patterns, and own how the platform shows inside customer environments at scale. Operating as a peer of engineering, security, and architecture leaders, you will hold the views of end users, enterprise compliance teams, and platform engineers simultaneously, making trade-offs explicit and driving measurable improvement in customer time-to-deploy across new enterprise environments.   Responsibilities   Own the platform’s identity model for AI Co-Workers across organizational identity, infrastructure-level service authentication, and downstream-system authentication, evolving it to meet the needs of regulated enterprise customers   Define and maintain the supported-deployment posture across major public-cloud environments, including which patterns the platform supports natively, where customer substitutions are accommodated, and where the platform draws the line   Build and own the disciplined product process by which customer-specific deployment variations are evaluated, tracked, and converged into standard platform patterns over time   Lead architecture reviews with enterprise customers, staying close enough to real deployments to know where the platform genuinely fits and where it needs to evolve   Own the platform’s external architecture story: deployment guides, security postures, and identity model artifacts that enterprise customers rely on to assess and approve the platform   Partner closely with engineering leadership to ensure the platform delivers a reliable experience for the engineers and architects who build and deploy AI Co-Workers on it   Own value risk and viability risk: ensure customers and engineering teams adopt the supported deployment path, and that the deployment model works for legal, security, sales, and finance   Minimum Qualifications   Demonstrated experience shipping a platform or enterprise infrastructure product that other engineering teams adopted as the easiest correct path   Deep familiarity with enterprise deployments at scale: IAM, managed identity, workload identity, secret managers, network egress, and scanning postures   Experience leading architecture reviews with enterprise customers and accurately distinguishing signal from noise in complex stakeholder conversations   Working fluency with how modern AI systems operate at runtime, with the ability to translate that complexity for enterprise security, compliance, and platform teams   Strong written communication skills, with a track record of producing