Jobs at Deepgram

Build and operate Deepgram’s deal desk, including approval matrices, pricing playbooks, credit and promotion guidelines, non-standard deal reviews, pricing analysis, Salesforce CPQ workflows, and audit-ready approvals. Partner with Sales, Customer Success, Product, and Finance on pricing, packaging, renewals, and revenue recognition. Use AI for first-pass deal reviews and continuously improve desk rules and processes.

Owns Deepgram’s North American events and field marketing portfolio, including 20+ trade shows, conferences, partner programs, executive events, roadshows, and account-based initiatives. Responsibilities include event strategy, budgeting, vendor and contract management, partner funding, brand activations, sales enablement, pipeline attribution, lead routing, ROI analysis, and post-event reporting. The role partners closely with Sales, Demand Generation, Product Marketing, alliances, and Marketing Operations, while developing AI-powered workflows and supporting the Deepgram Speak event series.

Owns marketing and go-to-market analytics, KPI definitions, attribution, campaign and sales-play measurement, scoring-model evaluation, dashboards, and weekly leadership reporting. The role reconciles Salesforce, HubSpot, and attribution data; partners with data teams on source-of-truth datasets; and builds AI-powered analytics agents, automated reporting, anomaly alerts, and data-quality processes to guide budget and pipeline decisions.

Lead technical sales for Deepgram’s Voice Agent platform, owning discovery, architecture, proofs of concept, technical evaluations, and customer production launches. Partner with account executives on enterprise deals, carry a growth quota, build demos and integrations, develop sales enablement, provide product feedback, and collaborate with telephony, contact center, and LLM partners. The role requires deep voice-agent expertise across telephony, orchestration, streaming pipelines, and speech and language models.

Supports and improves revenue operations systems and workflows, including quote-to-cash, CPQ, billing, subscriptions, Salesforce automation, data governance, forecasting, routing, quotas, and commissions. Partners with Finance, GTM Engineering, Sales, Customer Success, and Renewals to troubleshoot issues, reconcile data, automate repetitive processes, and improve commercial systems. The role also helps implement scalable processes and AI-enabled operational solutions.

Leads Deepgram’s GTM Engineering function, owning CRM, CPQ, forecasting, billing, data, integrations, automation, and internal tooling. Translates commercial needs into scalable systems and AI-powered workflows, establishes engineering standards, connects usage and revenue data, and partners with Product, Engineering, Finance, and Data teams. This player-coach role designs, codes, tests, ships production systems, and develops a small team while prioritizing automation and operational leverage.

Own Deepgram’s AI applications product line, including strategy, roadmap, customer definition, acquisition, activation, retention, monetization, and profitability. Lead zero-to-one product development, represent the product with customers and partners, and coordinate research, engineering, design, and marketing. Prototype and validate ideas through real usage and measurement while communicating decisions to executives. The role requires shipped, paid consumer or prosumer products, deep AI application experience, technical depth, design judgment, and strong product leadership.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Own technical go-to-market enablement for pre-sales and post-sales teams. Build onboarding, ramp programs, technical frameworks, playbooks, certifications, launch readiness, and scalable guidance from subject-matter expertise. Partner with Product, Applied Engineering, Customer Success, Sales, and PMM to improve technical discovery, evaluations, architecture guidance, handoffs, escalations, and customer readiness. Use AI, scripts, agents, and workflows to eliminate recurring work and scale enablement.

Design and refine feature-level UI for Deepgram’s Playground and Console products. Work within the Cosmos design system, support senior designers, own assigned features through production handoff, document design rationale, participate in critiques, and provide peer feedback. The role serves technical and developer audiences and encourages practical use of AI and design tools.

Own Deepgram’s privacy operations, security compliance, audit evidence, control mapping, security questionnaires, policies, and public trust documentation. Lead DPIAs, data-flow mapping, DSAR and deletion workflows, vendor reviews, SOC 2, ISO 27001, and PCI DSS audits. Partner with Engineering, Legal, Research, and Sales Engineering to verify technical claims, automate evidence collection, maintain accurate documentation, and translate privacy and AI regulations into practical requirements and enablement.

Owns Deepgram’s privacy operations program across hosted, dedicated, and self-hosted deployments. Leads privacy risk assessments, DPIAs, transfer impact assessments, data-flow mapping, records of processing, vendor reviews, retention and deletion controls, DSAR workflows, and privacy audits. Translates privacy and AI regulations into engineering and go-to-market requirements, develops operational playbooks and tooling, supports customer reviews, and partners with Legal, Security, Engineering, and Sales Engineering to produce verifiable privacy evidence.

Build and automate security controls across bare-metal Linux infrastructure and AWS. Responsibilities include host hardening, vulnerability and patch management, container and CI/CD security, penetration testing, detection and incident response, access and log reviews, compliance evidence automation, and software supply-chain security. The role also supports customer security work and applies AI tooling to security operations.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Design and implement secure, scalable backend services for voice agents, integrate AI models and telephony, improve inference, debug concurrent systems, and collaborate with Product to deliver features end-to-end.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

Own and grow the self-serve developer funnel from first touch to paid customer. Define and ship product changes across onboarding, console, and activation. Build instrumentation, experimentation, and business rhythms; run rapid hypotheses, measure outcomes, and collaborate with engineering, design, dev rel, marketing, sales, and analytics.

Own adoption, retention, and expansion across a pooled portfolio of scaled customers through digital-first programs. Provide technical API integration guidance, troubleshoot issues, run demos, and create reusable enablement assets. Design automated customer journeys, webinars, self-service resources, and workflows that accelerate activation. Monitor usage and health data, identify expansion opportunities, report KPIs, and build scalable systems that reduce recurring manual work.

Design and implement secure, scalable backend services for speech inference and audio processing. Optimize networking, transcoding, latency, memory, and distributed compute orchestration. Measure and improve system performance, debug complex networking/scheduling/HPC issues, customize services for customers, and partner with Product to deliver features end-to-end.

Design and implement scalable, secure inference services for speech processing. Optimize networking, audio transcoding, latency, memory, and distributed compute orchestration. Debug complex system issues, customize backend services for customers, and partner with Product to deliver end-to-end features.