Engineering Manager, Enablement

Why this job is exciting

The role:

Reporting directly to the SVP of Engineering, the Engineering Manager - Engineering Enablement will build and own the Engineering Enablement team at Capacity. Your team's primary mission is to develop AI-powered processes and tooling that accelerate engineering velocity across the entire organization. This includes the AI pairing pipeline, the automated ticket generation workflow, the non-engineer contribution program, and the broader developer tooling infrastructure that makes every engineer faster. You will work closely with the Engineering Program Manager and the VP of Engineering to ensure the Enablement team's output is directly connected to the velocity goal.

Responsibilities

• Build and lead the Engineering Enablement team: a small, high-leverage team whose output is felt by every engineer in the organization.
• Design, build, and operate the AI pairing pipeline that enables every engineer at Capacity to work with AI as a genuine productivity partner, not just an autocomplete.
• Build the automated ticket generation workflow that converts product and operational signals into sprint-ready tickets with minimal human intervention.
• Own the non-engineer contribution program: formalizing and scaling the process that allows Product Managers, Customer Success engineers, and other technical contributors to safely commit code.
• Establish engineering standards, guardrails, and best practices for AI-assisted development across the organization.
• Build the developer tooling infrastructure that reduces friction in the day-to-day engineering experience from local development to deployment.
• Measure the impact of every Enablement investment in terms of velocity and quality and iterate relentlessly based on what the data shows.

Requirements

• 8+ years of software engineering experience, with a strong background in developer tooling, platform engineering, or internal infrastructure.
• Demonstrated experience building AI-assisted engineering workflows including prompt engineering, LLM integration, and evaluation frameworks for AI-generated output.
• Experience building and operating automation pipelines that reduce manual work at scale.
• Strong understanding of the software development lifecycle and the specific friction points that slow engineering teams down.
• Experience in a technical leadership or staff-level engineering role with cross-team influence.
• Familiarity with modern AI developer tools including Claude, Cursor, GitHub Copilot, and similar platforms.
• Experience building low-risk code contribution workflows for non-engineers is a strong plus.
• Strong data and measurement orientation: able to define success metrics and track them rigorously.

What you can expect from us

• The team:
• We provide:
• Engineering
• Remote (United States)