Applied AI Platform & Chatbot Product Lead

White & Case LLP

Greater London

On-site

GBP 110,000 - 150,000

Full time

14 days+

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Job summary

White & Case LLP in London is seeking an entrepreneurial product leader to own Atlas Platform and Atlas Chatbot. You will shape the roadmap, balance user needs with security and cost, and work with engineers, security and risk teams to deliver scalable AI solutions across the Firm.

This hands-on role requires rapid prototyping, real‑world testing and a startup mindset within a global law firm. You will move between strategy, workflows and technical implementation, ensuring governance, compliance

Qualifications

Substantial hands-on software product management experience in a startup, scale-up or similarly autonomous team.
A track record of shipping products and improving their adoption and value after launch.
Strong product judgment, user research and analytical skills, with the confidence to challenge assumptions and prioritise.
Ability to turn experimental results into clear product decisions, including when to iterate, stop, productionise or scale an approach.
Experience working directly with engineers as a technical peer; with the ability to prototype solutions, discuss APIs, integrations, shared platform capabilities and delivery trade-offs.
Practical experience using AI-assisted development tools to accelerate learning, prototyping, review, testing or documentation.
An active interest in applied AI, an ability to learn quickly, and sound judgment around sensitive data and consequential workflows.
Clear communication and the ability to establish priorities with senior stakeholders while keeping delivery moving.

Responsibilities

Own distinct but coordinated roadmaps for Atlas Platform and the chatbot, balancing user needs, shared capabilities, reliability and cost.
Translate user problems and operational needs into testable hypotheses, working prototypes, evaluation plans and clear product requirements.
Take ownership of selected applications after initial validation, establishing their roadmap, launch plans and ongoing product direction.
Build rapid, functional PoC using AI‑assisted development tools to validate workflows and features before production investment.
Use AI‑native workflows across discovery, prototyping, implementation, review, testing and documentation to increase the speed and quality of product development.
Work with Technology, security and risk colleagues to translate requirements for permissions, ethical screens, client restrictions and auditability into platform priorities and acceptance criteria.
Prioritise platform integrations with engineering and system owners, making reusable connections available to multiple AI applications through the Firm’s MCP gateway.
Understand the needs of both end users and teams building on the platform; turn their feedback into testable hypotheses, working prototypes and clear product requirements, then work with engineers to productionise successful approaches.
Measure platform reliability, integration lead times and reuse alongside chatbot task success, adoption and operating costs.
Share prototypes and evaluation evidence with engineering, security and risk teams to support decisions about productionisation, controls and scaling.
Coordinate release readiness and adoption, resolving dependencies across delivery partners, operational teams and the wider business.