Forward Deployed Product Manager

Caylent is an AI-first cloud services company that helps organizations turn ambitious ideas into meaningful business impact. The Forward Deployed Product Manager will lead the product workstream in client engagements, guiding product teams through transformation and enabling AI-assisted development.

Responsibilities:

• On enterprise transformation programs, lead the product workstream end-to-end: assess how client product teams operate today, design the future-state PDLC, and coach PMs through the shift from spec authors to strategic orchestrators of AI-assisted development
• On prototype and build-enable engagements, anchor the product side: run discovery with client stakeholders, shape the delivery backlog into a signed Sprint Charter, and write the specs that drive prototype and MVP development
• Design PM training curricula and lead enablement sessions throughout engagements, using real delivery work as session material
• Surface expansion opportunities during delivery: by the close of each engagement, you have a clear view of what the client's product org needs next
• Help define and refine the product-facing agents Caylent deploys across engagements: idea consolidation, spec generation, PM workflow automation, and the product side of advanced agent prioritization
• Provide field feedback that sharpens agent design, prompt configuration, and the scoping frameworks that determine where agentic tooling fits in client environments
• Co-own the product spec artifacts that define how Caylent's IP gets built and evolved across the practice
• Turn PDLC patterns from the field into improvements to product workstream methodology, scoping frameworks, and future-state design templates
• Support pre-sales conversations where product definition, sprint structure, or PDLC maturity assessment is part of the qualification

Requirements:

• 7+ years of product management experience, including meaningful time in a client-facing, embedded, or consulting role
• Experience working directly with product teams on how they work: their discovery processes, PDLC design, and spec practices
• Experience or demonstrated capability in the use of Agentic AI to facilitate product management activities
• Strong facilitation: you run working sessions with product and engineering stakeholders, extract useful signal from ambiguous input, and drive toward a signed-off decision
• Able to write clean, executable specs, both for your own engagement deliverables and as a model for clients you're coaching
• Technical fluency to scope prototypes with engineers: you can discuss architectural feasibility, participate in spec-to-build handoffs, and hold your own in an architecture lock session
• Background in professional services, management consulting, or an embedded advisory role
• Experience redesigning how a product function works inside another organization, not just producing recommendations
• Familiarity with AI-native product workflows: spec-driven development, LLM-assisted requirements generation, or agentic product tooling
• Experience with PE portfolio company environments or enterprise engineering organizations navigating modernization
• Hands-on familiarity with Claude Code or equivalent AI-assisted development tooling