Senior AI Product Manager

Requirements

• 7+ years of experience spanning software or ML engineering and product development, or a closely related combination — we value technical depth and product ownership in equal measure
• Demonstrated hands‑on experience building with LLMs and/or agentic frameworks — shipped products or features preferred over academic work
• Working knowledge of how large language models and agentic systems behave in production - including tool use, prompt design, orchestration patterns, output variability, and failure modes
• Ability to write clear product requirements and define, review, and challenge technical specifications without requiring engineering support
• Experience evaluating and testing AI outputs — defining acceptance criteria, identifying edge cases, and working with engineering teams to resolve model or integration issues
• Solid Python skills and familiarity with APIs, data pipelines, and cloud infrastructure
• Experience with real-time or near-real-time data systems, with a natural sensitivity to latency, throughput, and cost trade-offs
• Familiarity with responsible AI principles — including data quality, model performance monitoring, and bias considerations — and their implications for product design in regulated environments
• Comfortable working across technical and commercial stakeholders — able to translate product decisions clearly for engineering teams and client-facing audiences alike
• Exposure to AI partner platforms or ecosystems in a product, technical, or commercial capacity is an advantage
• BA, BS, or Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience

What the job involves

• We are looking for a hands‑on AI Product Co‑Developer to join our team building production‑grade agentic AI systems for complex, data‑intensive environments
• This is a hybrid role sitting at the intersection of product thinking and engineering depth — you will both define what gets built and actively build it, working across the full lifecycle from discovery and requirements through to deployment and iteration
• Contribute to the full AI product lifecycle: discovery, requirements definition, development, testing, and deployment
• Design, build, and iterate on LLM-powered agentic workflows for complex, data‑intensive use cases, applying sound orchestration patterns and tool‑use design
• Translate business and user needs into clear, actionable product requirements and agent configurations
• Define and monitor product performance metrics and acceptance criteria for AI outputs in production — covering accuracy, latency, cost, and auditability
• Manage the post‑launch product lifecycle: track performance, gather user feedback, and contribute to model or feature refresh cycles
• Contribute to system optimisation across performance, cost, and operational constraints
• Collaborate with governance teams to ensure AI outputs meet internal quality, compliance, and interoperability standards
• Maintain a forward‑looking view on the evolving AI landscape — including model capabilities, agentic frameworks, and emerging protocol standards — and translate relevant developments into product opportunities
• Engage with internal stakeholders and cross‑functional teams to support successful delivery of AI capabilities
• Support demos and presentations of prototypes and new capabilities to internal and external audiences
• Build and share expertise in AI product design and agentic workflows across engineering, product, and domain teams