Federal Civilian AI Sales Executive

Bazeta; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Deepgram is hiring a Strategic Account Executive, Federal Civilian Agencies, to build and grow the civilian agency book. You will own strategy and execution for named agency accounts, driving direct, partner-assisted, and channel-enabled motions to land AI-native solutions.

The role emphasizes landing inside mission programs, building measurable pipeline, and navigating federal procurement. Remote work and a fast-paced AI-driven environment are expected.

Qualifications

• Must be a U.S. citizen.
• 5+ years of full-cycle sales experience, with at least 3 years selling to Federal Civilian agencies (enterprise SaaS/technology).
• Proven track record of meeting or exceeding quota in complex federal sales cycles.

Responsibilities

• Own the Federal Civilian go-to-market strategy for named agencies.
• Build and execute account plans with stakeholders across programs, tech, and contracting.
• Drive direct, partner-assisted, and channel-enabled motions to qualify, propose, and close opportunities.
• Coordinate with Federal Partnerships, Legal, and Applied Engineering to remove friction and accelerate revenue.
• Develop compliant, compelling responses to RFPs and sole-source opportunities.
• Maintain a measurable, quota-carrying pipeline and CRM-based forecast.
• Represent Deepgram at agency industry days, conferences, and events.
• Provide regular pipeline dashboards and honest monthly/quarterly narratives.

Skills

Federal sales

SaaS sales

Strategy development

Job description

Deepgram is hiring a Strategic Account Executive, Federal Civilian Agencies, to build and grow the civilian agency book. You will own strategy and execution for named agency accounts, driving direct, partner-assisted, and channel-enabled motions to land AI-native solutions.

The role emphasizes landing inside mission programs, building measurable pipeline, and navigating federal procurement. Remote work and a fast-paced AI-driven environment are expected.