Senior AI Product Manager | UK in London

Who We Are

At Supermodular AI, we help enterprises navigate AI Transformation. We believe in strategy through execution. Most organizations understand the potential of AI, but struggle to translate that ambition into real operational change. The challenge is rarely the technology itself. It is how AI fits into complex systems, workflows, and engineering organizations that have evolved over years. We believe AI transformation cannot be designed purely in strategy documents. The real strategy only emerges by building, deploying, and operating AI systems inside the organization. That’s why we work directly with enterprise IT and software teams to design and implement AI systems in real environments. This includes enabling engineering organizations to work in fundamentally new ways by introducing AI-native development practices, frameworks, and technical assets that change how teams build and operate software. It also includes building custom AI systems that unblock difficult modernization or harmonization efforts where traditional approaches have stalled. Our team has a strong track record of building high-impact AI systems and scaling engineering teams inside complex enterprises. If you enjoy solving hard enterprise problems and turning ambitious ideas into systems that actually run in production, you’ll feel at home at Supermodular AI.

Your Role

As AI Product Manager at Supermodular AI, you will operate at the intersection of problem discovery, AI system design, and hands‑on system building inside enterprise AI transformation initiatives. This role looks very different from traditional product management. You are not here to manage backlogs or coordinate delivery. You are here to build and shape AI systems. You will design and implement the first working versions of AI systems, agentic workflows, LLM‑based systems, orchestration logic, and evaluation loops, running inside real enterprise environments. You will move quickly from problem → system design → working implementation, using real data and operating within real constraints. You will work closely with Deployment Strategists and Forward Deployed Software Engineers, forming the core execution pod responsible for shaping problems, designing solutions, and delivering systems that run reliably in production environments. You will work directly with enterprise leaders, engineers, and operators to understand how their systems and workflows operate today, identify where AI can create meaningful improvements, and translate those opportunities into working systems. As systems begin running in production, you will also recognize where additional impact can be created, identifying new opportunities for AI and helping frame them into initiatives the team can pursue. This role is for someone comfortable operating in ambiguity, building quickly, and being accountable for working systems rather than documentation.

Desired Skills And Qualifications

• AI specialist judgment: you have strong intuition for what modern AI systems can and cannot do in practice, and you use that to choose the right problems and solution approaches.
• Problem + impact ownership: you can find the real bottlenecks inside enterprise workflows, define what impact means operationally, and keep the team focused on outcomes, not features.
• Enterprise stakeholder fluency: you’re comfortable working directly with enterprise leaders, engineers, architects, and operators, earning trust, navigating constraints, and driving alignment in messy orgs.
• Builder mindset: you don’t just describe systems. You build the first working versions (agentic workflows, orchestration, eval loops, integrations) and iterate until they work in the real environment.
• AI‑native solution design: you think agentic‑first, combining models, tools, retrieval, and workflows into coherent systems (not “LLM as a feature”).
• Reliability through evaluation: you treat AI as probabilistic and design guardrails, evaluation, feedback loops, and operational monitoring so systems behave predictably in production.
• Fast iteration under real constraints: you move quickly from ambiguity to a working system, using real data and enterprise constraints.
• Systems thinking across the stack: you can reason end‑to‑end across data, APIs, integrations, security constraints, and human workflows to design solutions that survive reality.
• Opportunity radar: while delivering, you continuously spot adjacent problems and new impact areas, validate them, and frame them clearly into next initiatives.
• Execution leadership: you can drive multiple pods forward, making trade‑offs, unblocking decisions, pushing back on mis‑scoped asks, and keeping the work shippable.

Hiring Process

Intro Interview > Technical deep‑dive > Culture & Offer