Role at a Glance
Customer-facing PM role at an early-stage London AI infrastructure company. You will translate enterprise client requirements into AI research priorities — and translate what researchers build back into outcomes customers trust. The function does not exist yet; you will shape it from the ground up. Fully on-site, London. Salary: £101,000–£192,000/yr. Visa sponsorship and relocation support available.
What This Role Actually Is
Callosum is hiring its first Applied AI Product Manager to serve as the connective tissue between enterprise clients and the research team building its intelligent systems. This is not a conventional PM post — there is no existing backlog to manage, no pre-defined roadmap to maintain. You will immerse yourself in a client's technical environment, map their real constraints and workflow structure, and carry that context into how Callosum's researchers and engineers prioritise work. You will also engage directly with senior client stakeholders, which means technical credibility is a baseline expectation, not a bonus.
About Callosum
Callosum was founded on the premise that the dominant AI scaling strategy — larger homogeneous models running on identical chips — is reaching its limits. Their thesis: genuine capability requires heterogeneous infrastructure, where diverse models run on diverse silicon and co-evolve into systems where intelligence emerges from the interaction of components rather than from any single one. The company launched publicly in early 2026 reporting order-of-magnitude benchmark gains. Their primary focus is agentic AI — multi-step, long-horizon systems operating in dynamic environments. The team is an in-person group of engineers and scientists in London, working across the full compute and model stack.
What You Will Own
- Translate enterprise client workflows, constraints, and requirements into clearly scoped problem definitions that Callosum's research team can act against
- Serve as the primary technical point of contact for senior stakeholders within customer accounts, owning those relationships end to end
- Carry customer deployment context across internal teams — research, applied AI engineering, and benchmarking — so each group has what it needs to prioritise effectively
- Define what a successful product deployment looks like for each client based on their specific use case, not a one-size-fits-all template
- Establish the methodology and engagement standards governing how Callosum works with enterprise customers — this infrastructure does not yet exist and you will build it
Must-Have Qualifications
- Technical foundation sufficient to read code, follow architecture discussions, and reason about how agentic AI systems are structured and deployed — typically a CS or STEM degree, or equivalent depth acquired another way
- 5+ years of experience in technology or strategy consulting with enterprise clients, or in venture and operating roles with comparable enterprise exposure, having pursued a customer-facing path rather than software engineering
- Demonstrated track record of operating in front of senior decision-makers at large organisations
- Genuine comfort working without a playbook in an ambiguous, early-stage environment where the function itself is being defined
Differentiating Experience
- Consulting work that placed you inside a client's codebase or embedded alongside their engineering team — hands-on technical engagement, not stakeholder management alone
- Prior customer-facing PM experience at an AI-native or agentic AI product company
- Practical experience deploying or operationalising LLM-based systems within an enterprise environment
- Strong academic record from a leading technical or scientific programme
Skills Breakdown: Required vs. Beneficial
The non-negotiables cluster around technical depth and enterprise access. You must be able to read code and reason about AI system architecture, and you must have a verifiable track record in front of senior enterprise stakeholders — consulting or operating experience is the most common path in. Ambiguity tolerance is not a soft skill here: the function has no playbook, so first-principles operating is a hard requirement. On the beneficial side, hands-on LLM deployment experience and AI-native company background are meaningful differentiators — they shorten ramp time in Callosum's agentic systems context considerably.
Salary and Compensation
Callosum lists a salary range of £101,000–£192,000 per year. The wide band reflects flexibility on candidate seniority level and the early-stage nature of the company; the final figure is determined by skills and experience. Beyond base pay, the package includes equity ownership — which at a funded pre-scale AI startup carries meaningful long-term upside — plus private healthcare. Visa sponsorship and relocation assistance are explicitly offered, indicating Callosum is conducting a global talent search rather than restricting the candidate pool to UK residents.
Benefits
- Equity and ownership stake in the company
- Private healthcare coverage
- Visa sponsorship for candidates requiring UK work authorisation
- Relocation support for candidates moving to London
- In-person London office with tooling and workspace setup configured for focused technical work; specific working needs accommodated on request
Location and Work Model
This role is fully on-site at Callosum's London office — the team works in person by design and the job description makes no provision for remote or hybrid arrangements. For candidates outside the UK, Callosum provides both visa sponsorship and relocation support, making the position genuinely accessible to international applicants. If you have specific workspace requirements, the company invites you to raise them directly.