Forward Deployed Engineer

Caylent

8h•$175,000 - $195,000•Remote

About The Position

Caylent is a global, fully remote cloud native services company specializing in Amazon Web Services (AWS), including workload migrations, cloud native application development, DevOps, and data engineering. This role is within Caylent’s Anthropic Business Unit, a dedicated AI services practice built in partnership with Anthropic. The Agentic Architect serves as the strategic and architectural lead on AI engagements, working in tandem with a Forward Deployed Engineer (FDE) who handles implementation. This cross-functional position involves shaping AI strategy, designing operating models, mapping AI outcomes to business value, and guiding executive stakeholders through the adoption of AI, with a focus on Anthropic’s platform. Clients range from PE portfolio companies and growth-stage software businesses to enterprise organizations, with the Agentic Architect acting as the strategic face of Caylent throughout the engagement lifecycle.

Requirements

8+ years of software development or technical architecture experience across varied stacks, including hyperscaler environments
3+ years in engineering leadership, technical consulting, solutions architecture, or a combination
Demonstrated ability to engage across lines of business
Experience designing or advising on AI operating models, technology adoption strategies, or digital transformation programs
Hands-on familiarity with Claude Code or equivalent AI-assisted development tools
Certified Claude Architect
Experience running structured stakeholder interviews, discovery sessions, and facilitated workshops with both technical and business audiences
Strong executive communication: writing and presenting to CTOs, VPs of Engineering, and line-of-business leaders
Experience delivering professional services engagements, including scope management, deliverable ownership, and client advisory
Working knowledge of CI/CD pipelines, DevOps practices, and modern software development workflows

Nice To Haves

Experience mapping AI initiatives to business outcomes (revenue, efficiency, risk, time-to-value) with executive-level ROI framing
Familiarity with PE portfolio company environments and board-level communication
Background in solutions architecture, platform engineering, or enterprise technology strategy
Experience with LLM prompt engineering, agentic AI workflow design, or AI product development
Direct experience with Claude Code’s extensibility model
Familiarity with SDLC maturity frameworks or workforce analytics (DORA, DevEx)
Experience designing and facilitating workshops for mixed audiences — engineers, product managers, and business stakeholders

Responsibilities

Own AI engagements end-to-end as the strategic lead, from discovery through executive handoff, partnered with an FDE who drives implementation
Run structured discovery across engineering, product, and business stakeholders to map organizational context, AI readiness, and strategic goals across lines of business
Design AI operating models that define how the organization adopts, governs, and scales AI
Define AI outcome maps that tie initiatives to measurable business results: efficiency gains, revenue impact, risk reduction, and time-to-value
Lead AI maturity assessments and architect near-term and long-term adoption roadmaps aligned to Anthropic’s platform capabilities
Facilitate executive workshops and enablement sessions for audiences ranging from engineering teams to C-suite leaders
Deliver executive presentations to CTOs, VPs of Engineering, and line-of-business leaders covering current-state findings, ROI projections, and strategic recommendations
Direct FDE work on Claude Code tooling, prompt architecture, and workflow automation
Identify expansion opportunities across lines of business
Shape follow-on scope throughout the engagement
Build executive relationships that position Caylent as a long-term AI strategy partner
Attend on-site for the final Catalyst block: readout, workshop, and executive presentation
Contribute reusable strategy frameworks, delivery artifacts, and methodology improvements back into the practice at engagement close
Lead AI strategy engagements spanning multiple teams, platforms, and business functions
Collaborate with FDEs to refine the architect-engineer delivery model and improve handoff patterns