Director Software Engineering - Agentic AI

Equinix Incubation builds the agentic systems that run the software delivery lifecycle end to end: a fleet of specialized AI agents, with humans directing the work and owning every gate. Someone has to own the product, the roadmap, and the team behind it. That is this role.

You will lead the engineering pods that build the orchestration layer, the persona consoles, and the agents themselves, and carry the roadmap from first MVP to organization-wide scale. This is a player-coach role for a leader who can hold a product vision, an architecture, an executive audience, and a hiring plan in their head at the same time.

Responsibilities

Own the Product and the Roadmap

• Define and drive the delivery-engine roadmap: orchestrator, agent fleet, consoles, dashboards, and enterprise integrations, sequenced for value
• Make the build-measure-learn loop real: ship in sprints, pilot with live delivery teams, and let adoption and telemetry reshape the plan
• Own trade-off decisions across scope, quality, cost, and speed, and defend them with data in front of senior leadership

Build and Lead the Pods

• Hire, grow, and retain a small, exceptional team of agent engineers, platform engineers, and delivery talent across the UK and India
• Run lean pods where agents do the routine work and people do the judgment work; model that way of working yourself
• Set a high, kind bar: clear expectations, honest feedback, and career growth in the most modern engineering discipline there is

Prove the Value

• Own the value story: cycle time, throughput, quality, adoption, and realized business value, instrumented and reported without drama
• Keep the economics honest: agent cost, platform cost, and capacity unlocked, treated as first-class engineering metrics
• Turn pilot wins into an expansion case that finance and function leaders believe

Set the Operating Standard

• Establish how agent-first engineering is done: evals as release gates, human-in-the-loop approvals, and responsible AI governance with InfoSec and the AI council
• Represent the platform in architecture and governance forums, and keep the roadmap aligned with enterprise platform and data strategy
• Share patterns, standards, and playbooks so other teams can adopt what your team proves

What Success Looks Like

• The delivery engine is in daily use by live delivery teams, with measurable cycle-time and quality gains that survive finance scrutiny
• You have built a team people want to join, with a hiring record and retention that show it
• Executives trust your roadmap because what you commit to ships, and what ships gets measured
• The operating standards your team set are being adopted beyond your team

Qualifications

• 12+ years in software engineering, including 5+ years leading engineering teams or engineering-led products
• A record of shipping and scaling platforms or products in an enterprise, from first release through adoption
• Hands-on fluency with modern AI: LLM-powered applications, agentic systems, and what it takes to make them production-grade
• Strong architectural judgment across APIs, event-driven systems, cloud platforms, and enterprise integration
• Proven hiring and talent development record, including building distributed teams
• Executive-grade communication: you can carry a room of senior stakeholders with a clear, honest narrative

Preferred Qualifications

• Experience delivering AI or automation platforms into regulated or security-conscious enterprises
• Experience with agent frameworks and protocols such as MCP or A2A, and with eval-driven quality practices
• Experience running product operating models: roadmaps, funding cases, value realization
• ·Background in developer platforms, SDLC tooling, or engineering productivity

Core Competencies

• Product & Technical Leadership: Proven ability to own and execute product roadmaps, make sound architectural decisions, balance trade-offs between scope, quality, speed, and cost, and apply systems thinking to solve complex business and technology challenges.
• People Leadership: Strong track record of hiring, developing, and retaining high-performing teams, fostering a culture of coaching and continuous growth, and successfully leading distributed engineering organizations across geographies.
• AI-First Operating Model: Deep understanding of agent-first ways of working, AI governance and evaluation frameworks, human-in-the-loop operating models, and the ability to measure and demonstrate business value through data-driven outcomes.
• Executive Influence: Excellent communication and stakeholder management skills, with the ability to build alignment across business and technology leaders, create compelling business cases, and confidently navigate executive discussions and decision-making.