Deepgram

2 weeks 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: 4.5

Website LinkedIn Glassdoor

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Deepgram

2 weeks 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

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

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: 4.5

Website LinkedIn Glassdoor