Forward Deployed Product Manager

Caylent's Anthropic Consulting and Engineering (ACE) practice is a dedicated AI services team built in partnership with Anthropic. We are Anthropic's first pure-play delivery partner.

The Agentic SDLC Product Manager owns the Product workstream inside client engagements. On Transformation Blueprint programs, you lead the Product workstream alongside engineering and organizational workstream leads: running current-state assessments with client product teams, designing the future-state PDLC, and coaching product managers through the shift from spec authors to strategic orchestrators of AI-assisted development. On 3-2-1 Build and Enable engagements, you shape the prototype: leading the scoping session, defining the Sprint Charter with the client, and driving the spec generation that feeds Sprint 1 delivery.

You are embedded in client product and engineering organizations from kickoff through handoff. Your clients are product managers and engineering leads who need to redesign how products get built, not just which tools their teams adopt.

• 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

• 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

• Operates inside the client's product function. You're in the roadmap sessions, the scoping workshops, and the spec reviews. Clients let you in because you understand their problems.
• Makes client PMs better. Your measure of success is whether client product teams can run AI-native workflows after you leave.
• Owns the diagnosis and the design. You run the assessment, draw the conclusions, and write the future-state design.
• Can build a sprint with engineers. On prototype engagements, you're defining the Sprint Charter and writing the specs. You can hold a technical conversation about feasibility and push back when scope doesn't fit the architecture.
• Feeds the methodology. Every engagement teaches you how product organizations respond to AI-native practices. You turn that into the next version of the workstream approach.

This is a poor fit if you're most comfortable in a single-product company where your users are internal and your roadmap is yours to own long-term. Engagements close. You hand off and move to the next client. The quality of what you leave behind is the measure.

• The Product workstream is one of the most differentiated parts of the Transformation offering and currently the one with the most room to develop. You shape it from the first engagement
• Each engagement feeds directly back into the workstream materials: field observations change how the offering runs
• Your clients are PE portcos, enterprise engineering orgs, and Anthropic-referred customers at the frontier of AI adoption
• AI-native by default: you build with and through Claude, coaching clients on practices you use yourself
• Outcomes, not hours: advancement tied to workstream delivery quality, methodology contribution, and account expansion

Caylent is an equal opportunity employer.