Forward Deployed Product Manager

Role Overview

• Embed inside a Forward Deployed Experience Pod, working shoulder-to-shoulder with the client to learn the real workflow before you redesign it.
• Own the workflow, KPIs, and alignment for your pod. Define success metrics with the executive sponsor at week one, then build until you hit them. Measure outcomes against KPIs, not features shipped.
• Redesign the human experience around AI, not the other way around.
• Break a complex business problem into composable, shippable work the pod can ship in days, not quarters. Production progress every day.
• Work in your client's stack alongside the Forward Deployed Engineer and Forward Deployed Experience Designer in your pod.
• Pair with the Valtech leadership and your client's executive sponsor(s) to clear the path in real time. Legal, compliance, architecture, risk, governance, internal politics.
• Govern, secure, and measure outcomes from day one. AI in production demands real attention to evals, guardrails, and human-in-the-loop design. You own the framework that proves the solution works and keeps working after the pod rolls off.
• Transfer ownership cleanly. By the end of the engagement, the domain expert is set up to run the solution long-term without the pod. Documentation, conventions, and the team rituals that sustain the change are part of what you ship.
• Surface the next opportunity from inside the work. Embedded pods see what's broken next before anyone else does. You bring that signal back, so the pod earns its way into the next problem rather than waiting for procurement.
• Contribute to the evolution of Valtech's FDE practice. Every pod is a learning loop. Share what works, what didn't, and the patterns that should harden into how we deploy across clients.

Requirements

• Demonstrable experience as a senior Product Manager in a digital consultancy, product organization, or embedded-team environment, with a track record of shipping production software, not just running discovery.
• T-shaped skill profile. Product is your deep specialty, but you have enough hands-on experience in engineering and UX design to be a contributor in these spaces, not just conversant. You can read and reason about code, prototype an interaction in Figma, and hold your own in technical and design trade-off conversations.
• Proven experience taking AI or ML solutions from concept into production, not just pilot. You understand why most AI pilots never reach production, and you have direct experience navigating the people, process, and governance problems that cause it.
• Hands-on fluency with modern AI tooling across the SDLC: AI-assisted requirements and synthesis, prototyping with tools like Figma Make or Claude, AI-accelerated development pairing with engineers, agent evaluation frameworks, and the practical judgment to know what's production-ready and what isn't.
• Strong executive presence paired with hands-on credibility. Equally effective in a working session with two engineers and an executive sponsor review. You earn trust quickly inside client teams and operate as a partner, not a vendor.
• Proven ability to break ambiguous business problems into composable, shippable units of work and sequence them for daily progress. Comfort pressure to demonstrate value continuously, not at the end of a long cycle.
• Solid commercial awareness. Comfortable with milestone-based engagements where the pod is accountable to deliverables, not hours.
• Experience in modern delivery environments, with the ability to adapt the operating model to the engagement rather than apply a framework rigidly. Equally comfortable when there is no backlog, no rituals, and no playbook yet.
• A track record of leaving teams stronger than you found them. The FDE model is built on capability transfer, so the ability to coach a domain expert into ownership is part of the job, not a bonus.

Tech Stack

• SDLC

Benefits

• Growth opportunities
• Values-driven culture
• International careers
• Chance to shape the future of experience