AI Director

Head of Agentic Development

About the Role

The organization is driving a transformation to agentic development. The future is one where AI is not an add-on to the engineering workflow but the primary way software is built, tested, deployed, and maintained. This role leads that transformation end-to-end. The Head of Agentic Development owns the strategy, enablement, and measurement required to move the software development lifecycle from AI-assisted coding to AI-native software delivery.

This is not a tools procurement role. It is a leadership role that requires a highly opinionated view of what the agentic development workflow should look like across the full lifecycle, and the ability to drive the organization toward it. This leader will be accountable for changing how software is built, with measurable outcomes tied to delivery velocity, quality, and developer experience.

What You Will Own

Agentic Development Strategy and Roadmap

Define and execute the roadmap for the transition to agentic development. Own the vision for how AI reshapes every stage of the software delivery lifecycle, from requirements decomposition through code generation and review to testing, security, deployment, and operations. Set the pace and sequence for adoption, balancing ambition with the trust-building required for teams to embrace fundamentally new workflows.

Developer AI Tooling Strategy

Partner with engineering enablement, product leadership, architecture, and AI teams to shape the portfolio of AI development tools and emerging agentic coding platforms. Bring a transformation perspective to build-vs-buy decisions. Determine which capabilities become core engineering platforms, which remain experimental, and which should be retired.

Agentic Development Governance and Alignment

Establish and lead the governance structure for agentic development across the organization. Identify and connect the right leaders to drive progress, maintain alignment, and ensure successful practices scale across teams.

Standards, Skills, and Developer Infrastructure

Partner with engineering enablement, enterprise architecture, AI teams, and engineering leadership to build the infrastructure that enables effective agentic development. This includes AI context layers, reusable skills, verification frameworks, quality controls, shared libraries, and learning programs that accelerate adoption.

Engineering Community and Adoption

Build and sustain the internal community around agentic development. Create forums for sharing wins, surfacing challenges, and spreading best practices. Work with early adopters and skeptics alike to drive meaningful, sustained change measured by outcomes.

AI Usage and Cost Governance

Own the strategy for managing AI usage, compute consumption, and associated costs as agentic workflows scale. Ensure visibility, responsible adoption, and governance are built into the workflow.

Measurement and Accountability

Define success metrics and own measurable outcomes, including engineering velocity, software quality, developer experience, and the percentage of work completed through AI-native workflows.

Key Responsibilities

• Define and own the transformation roadmap for agentic development

• Lead governance structures that keep teams aligned and moving forward

• Partner across engineering, product, architecture, and AI teams on tooling and standards

• Build shared infrastructure that enables effective AI-assisted and AI-native development

• Establish metrics for delivery velocity, quality, and adoption

• Build communities and feedback loops around new engineering practices

• Partner on training programs that support broad adoption

• Own AI usage strategy, reporting, and cost governance

What We Are Looking For

Differentiating Skills

• Deep understanding of the full software delivery lifecycle and a clear vision for how AI transforms it

• Proven ability to drive adoption of new practices across a large organization

• Comfort operating in ambiguity while creating structure and momentum

• Ability to connect engineering teams, product leaders, architects, and executives

Foundation

• Strong technical fluency in modern software development and AI-enabled engineering workflows

• Experience with AI development tools, agentic coding frameworks, LLM-powered development, and supporting infrastructure

• Track record delivering platform capabilities or enterprise transformation programs

• Experience leading in fast-moving environments where new operating models are being created

• 10+ years of relevant experience; Director-level background preferred

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