Director of Field Engineering, Agent Builder

Decagon•San Francisco, CA

8d•Onsite

About The Position

As Director of Field Engineering, you will lead Decagon’s technical delivery for strategic enterprise customers—owning outcomes across multiple deployments and building the team, playbooks, and operating system required to scale. This is a senior, customer-facing leadership role where you’ll partner with customer executives and technical leaders to define success, translate requirements into delivery plans, and drive launches that measurably impact customer outcomes. You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM leadership to create tight feedback loops: driving delivery, surfacing product gaps, and influencing the evolution of Decagon’s agent-building platform based on real enterprise needs. This role is ideal for a leader who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on problem solving with structured execution at scale.

Requirements

10+ years of relevant experience in technical, customer-facing roles (e.g., forward-deployed engineering, solutions engineering, technical consulting, implementation engineering, technical product/PM, or similar).
5+ years of people management experience, including hiring, coaching, performance management, and building high-performing teams; ideally experience leading senior ICs and/or managers.
Strong technical foundation—comfortable working with APIs, integrations, and complex systems; able to go deep to diagnose issues and guide solution architecture.
Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration.
Ability to communicate clearly with senior technical stakeholders, translate requirements into execution plans, and drive delivery.
Comfort operating in fast-moving, ambiguous environments where you build structure while maintaining momentum.

Nice To Haves

Experience deploying LLM-based products or AI agents in production (prompting, evaluation, guardrails, tooling, workflow design).
Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and security/compliance considerations.
Strong product instincts—ability to define success metrics, write crisp requirements, and contribute customer insight back into product roadmap.
Experience scaling a delivery function from high-touch execution to repeatable playbooks and durable operating cadence.

Responsibilities

Lead and scale a high-performing delivery org
Own end-to-end execution of AI agent deployments for enterprise customers across a portfolio, from scoping through launch and iteration.
Build, lead, and develop a team of Agent Builders; hire, coach, and set a high bar for quality, velocity, and customer outcomes.
Establish delivery operating rhythms (planning, reviews, retros), capacity planning, and forecasting to ensure predictable execution.
Drive executive-level customer engagements
Interface with senior technical stakeholders and executives to define success criteria, align on constraints (security/compliance), and drive delivery against timelines.
Lead complex escalations and unblock cross-functional teams when quality, timelines, or customer outcomes are at risk.
Translate customer needs into crisp internal documentation and execution plans across Product/Engineering/GTM.
Create repeatable playbooks and scale mechanisms
Define and standardize delivery methodologies and artifacts (e.g., AOP quality bar, launch readiness checklists, iteration loops).
Establish best practices for evaluation and guardrails to ensure safe, compliant, and predictable agent performance in real-world scenarios.
Improve tooling and processes to reduce time-to-launch and increase reliability across deployments.
Influence the platform roadmap through deployment insights
Identify recurring product/platform gaps and drive prioritization with Engineering and Product leadership.
Partner with internal teams to turn real customer needs into platform improvements that compound across deployments.