Head of AI Enablement Engineering

Deepgram
California
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Communication","Influence","Product thinking","Adaptability","Cross-functional collaboration"]

Own AI enablement engineering end to end, turning Deepgram’s AI-native strategy into shipped, reusable capability across the company. You’ll evaluate and prototype AI tools and orchestration layers, build reference implementations (agents, skills, MCP integrations, paved-road workflows), and run the company-wide adoption strategy with measurable productivity and quality. Partner with Engineering, Platform/Internal Tools, Security, Data, and People Ops to define safe-use guardrails and scale a distributed champions network.

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FursaFursa
Deepgram
Deepgram
1 month ago

Head of AI Enablement Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 23 hours agoStatus: Live

Job Summary

Own AI enablement engineering end to end, turning Deepgram’s AI-native strategy into shipped, reusable capability across the company. You’ll evaluate and prototype AI tools and orchestration layers, build reference implementations (agents, skills, MCP integrations, paved-road workflows), and run the company-wide adoption strategy with measurable productivity and quality. Partner with Engineering, Platform/Internal Tools, Security, Data, and People Ops to define safe-use guardrails and scale a distributed champions network.
Location: California
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Director level

Key Responsibilities

  • •Own and drive AI enablement engineering strategy, standards, and hands-on building across the company.
  • •Evaluate and prototype AI tools, agents, models, and orchestration layers; make pragmatic build-vs-buy decisions.
  • •Build reference implementations including reusable agents and skills, MCP servers, paved-road workflows, and enablement hub assets.
  • •Set and run the company-wide AI adoption strategy using metrics and reporting framed around productivity and quality.
  • •Partner with Platform/Internal Tools, Security, and Data to define embedded safe-use guardrails and data-handling practices.

Key Requirements

  • •Strong engineering background with hands-on ability to build production-quality agents, tools, and automations.
  • •Deep, current fluency with modern AI tooling—coding agents, LLM application patterns, prompting, retrieval, MCP/agent tooling, and orchestration.
  • •Track record driving technology adoption and changing how people work at scale in environments that didn’t start out asking for it.
  • •Ability to operate across business and technical functions and influence without direct authority, with credibility with senior engineering leaders.
  • •Strong product and platform instincts for enablement as a product, with users, adoption, and a roadmap.
Experience:Voice AIDeveloper toolsAI enablement
Skills:CommunicationInfluenceProduct thinkingAdaptabilityCross-functional collaboration
Tech Stack:LLMPromptingRetrievalMCPAgent toolingOrchestrationAI agentsKnowledge toolingGleanNotion AI

Company Brief

Deepgram
Deepgram builds a real-time Voice AI platform delivering speech-to-text, text-to-speech, and voice-agent APIs for developers and enterprises, focusing on low-latency, high-accuracy voice models and scalable deployment options.
Industry: API Platforms
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series C
Headquarters: San Francisco, United States
Founded: 2015
Glassdoor
Glassdoor: 4.5
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