Director, Implementation (US)

Code and TheoryNew York, NY
$150,000 - $225,000

About The Position

The Machine is Code & Theory's AI orchestration platform — the engine that operationalizes AI across our work and, increasingly, across Stagwell, the global marketing and communications network Code & Theory is part of. The Machine integrates with the tools customers already use (Figma, Slack, Teams, Adobe, performance dashboards) and serves both Stagwell's internal agencies and enterprise brand customers including Qualcomm, TIME, and Stanley Black & Decker. We're looking for a Director of Implementation to own how the Machine lands inside customer and agency environments. This is the role that turns a powerful platform into working systems for real teams: scoping engagements, leading deployment, integrating with existing tooling, and driving adoption through to measurable outcomes. You'll lead a team of implementation engineers and solution architects, and you'll be the connective tissue between the platform's capabilities and what each customer needs from it. Our engineers are AI native and engage in and advance the state of the art in the practice of software development with AI.

Requirements

  • A track record of leading technical implementations or professional-services delivery for a software or platform product, ideally in environments with demanding enterprise customers
  • Strong technical fluency across cloud, integrations, and APIs — enough to architect a deployment, debug an integration, and earn the trust of the engineers you lead
  • Fantastic verbal communications and presentation skills, since this is a customer-facing role and you must have experience owning customer relationships through delivery, including the hard conversations about scope, timelines, and tradeoffs
  • People leadership experience, including in matrixed or cross-functional structures where influence matters as much as authority
  • A bias toward adoption and outcomes, with conviction about what separates a deployed tool from one a team actually uses
  • Comfort leveraging AI-enabled development tools and workflows to accelerate engineering, automation, debugging, and operational tasks
  • Experience orchestrating multi-step AI or agent-driven workflows, including selecting appropriate models, tools, and execution patterns for different use cases
  • Strong judgment reviewing and hardening AI-assisted output for security, scalability, maintainability, and architectural fit
  • Experience building or maintaining prompts, evaluation frameworks, documentation, or operational context systems that improve engineering velocity and reliability
  • Familiarity with automated evaluation and feedback loops for AI-enabled systems and workflows

Responsibilities

  • Own end-to-end implementation of the Machine across customer and agency environments, from technical scoping through deployment, integration, and adoption – you will write code and lots of it – daily
  • Stand up and lead a team of implementation engineers and solution architects, setting delivery standards and accountable for the quality and pace of every engagement
  • Translate customer requirements into deployment plans, working closely with the platform engineering team to surface gaps, prioritize integrations, and feed real-world needs back into the roadmap
  • Design integrations against the tools customers already run, making the Machine work alongside Figma, Slack, Teams, Adobe, performance dashboards, and the rest of a customer's stack
  • Drive adoption past go-live, defining what success looks like for each engagement and steering teams toward it with the right enablement, instrumentation, and follow-through
  • Partner across engineering, account, and customer stakeholders, coordinating reporting lines and expectations so delivery holds together as one effort
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