Senior AI Engineering Manager - Forward Deployed

Adobe Adobe · Enterprise · London, United Kingdom · Remote

Senior AI Engineering Manager at Adobe, leading a team of Forward Deployed AI Engineers and Creative Pipeline Specialists to build GenAI-powered content production systems for large brands. The role is player-coach, requiring hands-on coding (min 30% time), architecture decisions, and unblocking the team. Responsibilities include owning delivery outcomes, growing the team, setting technical direction, driving product feedback, scaling the organization through reusable capabilities, and representing the org externally. Requires 3+ years of management experience, hands-on GenAI experience (LLM integrations, RAG, agent frameworks), and experience in creative content supply chains. The role focuses on building and deploying AI systems that transform content production workflows.

What you'd actually do

  1. Lead by building. You are hands-on. You contribute directly to production systems — writing code, reviewing architecture, debugging deployments — especially when progress or clarity depends on it. Minimum 30% of your time is technical work.
  2. Own delivery outcomes. Drive end-to-end delivery across multiple customer engagements. Scope work, sequence delivery, remove blockers early, and make fast trade-offs between speed, scope, and quality. Every engagement ties back to measurable value realization and customer adoption — not just "we shipped it."
  3. Grow a high-performing team. Recruit, develop, and retain exceptional AI engineers. Set a high bar for performance. Give direct, actionable feedback. Build a culture of ownership, speed, and trust — not a culture of meetings and approvals.
  4. Set technical direction. Guide architecture decisions, enforce engineering standards, and ensure your team builds scalable, reusable systems — not throwaway consulting artifacts. You define what "production-ready" means.
  5. Drive the product feedback loop. Turn field-proven patterns into actionable product roadmap input. You sit at the intersection of customer reality and product strategy, and you make sure what your team learns in the field reaches the people building the product.

Skills

Required

  • Python
  • TypeScript/Node.js
  • React
  • LLM integrations
  • RAG pipelines
  • agent frameworks
  • building content production systems
  • MarTech platforms
  • asset automation tools
  • creative workflow technology
  • customer-facing leadership
  • technical workshops
  • stakeholder presentations
  • embedding with client teams

Nice to have

  • Cursor
  • Claude Code
  • Copilot
  • MCP servers
  • automated team processes with AI
  • AI agents to drive management workflows
  • technical founder
  • technical director at an agency
  • early engineer at a startup
  • globally distributed teams
  • introduced engineering practices (CI/CD, DORA metrics, code quality standards)

What the JD emphasized

  • You contribute directly to production systems
  • Minimum 30% of your time is technical work
  • You write and review production-grade code
  • You haven't "graduated" from engineering — you lead from within it.
  • Hands-on GenAI experience.
  • You've built or deployed AI-powered systems — LLM integrations, RAG pipelines, agent frameworks, or equivalent.
  • You understand how model behavior shapes product experience.
  • Creative content supply chain experience.
  • You know how creative teams work, how content gets produced at scale, and what breaks in the process.

Other signals

  • leading a team of AI engineers
  • building GenAI-powered content production systems
  • driving end-to-end delivery across multiple customer engagements
  • setting technical direction for scalable, reusable systems
  • turning field-proven patterns into actionable product roadmap input