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Job description
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TL;DR
Head of AI Enablement Engineering (AI): Driving the transition to an AI-native company by building reusable agents, workflows, and MCP integrations with an accent on operationalizing AI leverage across all functions. Focus on creating reference implementations, setting company-wide adoption standards, and designing safe-use guardrails for AI tools.
Location: Remote (USA)
Company
Deepgram is a leading platform for Voice AI, providing real-time APIs for speech-to-text, text-to-speech, and production-grade voice agents.
What you will do
- Drive AI enablement strategy and standards, building hands-on tools to increase AI leverage across every function.
- Evaluate and prototype AI tools, models, and orchestration layers to avoid tool sprawl and make build-vs-buy decisions.
- Create reference implementations, including reusable agents, MCP servers, and prompt and pattern libraries.
- Define and track company-wide AI adoption metrics focused on measurable productivity and quality.
- Partner with Security and Platform teams to embed safe-use guardrails and data-handling practices into internal systems.
- Build a distributed network of AI champions and scale a central enablement team over time.
Requirements
- Must be based in the USA.
- Strong engineering background with the ability to build production-quality agents and automations.
- Deep fluency in modern AI tooling: LLM application patterns, prompting, retrieval, and MCP/agent orchestration.
- Proven track record of driving large-scale technology adoption and changing how people work.
- Strong product instincts, treating internal enablement as a product with users, adoption metrics, and a roadmap.
- Ability to influence senior engineering leadership and communicate outcomes to executives in plain language.
Nice to have
- Experience starting an AI enablement, developer productivity, or engineering effectiveness function from scratch.
- Background in building internal platforms or developer-facing tooling that saw high adoption.
- Familiarity with enterprise AI search and knowledge tooling like Glean or Notion AI.
- Experience in a fast-moving, AI-native engineering organization.
Culture & Benefits
- AI-first culture where experimentation and the use of advanced AI tools are core to performance.
- High-visibility role with executive sponsorship and a mandate to set direction where no playbook exists.
- Fast-paced environment emphasizing rapid evolution, agility, and continuous learning.
- Philosophy of utilizing small, AI-leveraged teams to outbuild much larger organizations.
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