# Partner Success Engineer

**Company:** [Deepgram](https://hotfix.jobs/companies/deepgram)
**Location:** Remote
**Role:** Customer Success
**Salary:** $150k – $195k/yr
**Skills:** APIs, AI/ML, Speech-To-Text, Text-To-Speech, Voice Ai, Integrations, Live Demos, Architecture Design, Troubleshooting, Automation Tools, Dashboards, AI Workflows, Reference Architectures
**Posted:** 2026-04-24

> Drives technical adoption and expansion with strategic partners through hands-on enablement, demos, architecture guidance, issue resolution, and building scalable AI-powered systems for partner success. Blends sales engineering, account management, and customer success expertise in fast-paced remote environment.

## Job Description

## Responsibilities
- Act as a technical expert and strategic advisor to strategic partners, engaging directly with developers, engineers, and executives to align business goals with technical solutions.
- Build, nurture, and sustain partner and customer relationships across all personas interacting with Deepgram, from developers and program managers to CIOs, CTOs, and other C-level stakeholders.
- Conduct regular on-site visits with partners, work hands-on to drive adoption, and actively embed Deepgram into their workflows.
- Own and manage the full partner lifecycle: onboarding, adoption, technical enablement, expansion, and advocacy.
- Focus on making Deepgram successful in the partner ecosystem, ensuring products are integrated, enabled, and adopted effectively, applying best practices, reference architectures, and creative solutions to drive outcomes.
- Continuously operate in discovery mode, surfacing issues, deeply understanding their complexity and business impact, and translating them into actionable requirements for internal teams.
- Confidently run live product demos, guide architecture discussions, and troubleshoot L1-style issues, bridging the gap between technical support, solutions design, and commercial growth.
- Maintain a deep understanding of Deepgram APIs, integrations, and AI/ML technologies.
- Proactively identify and scope opportunities for expansion (cross-sell, upsell, multi-product adoption), partnering with Sales.
- Proactively initiate and lead executive business reviews, joint planning sessions, and strategy workshops to stay ahead of risks, ensure alignment, and surface opportunities for growth.
- Serve as the voice of the partner internally, influencing product roadmap, GTM strategy, and the internal tools and processes we build to support partners and customers.
- Lead issue resolution and serve as an escalation point for complex, cross-functional partner matters, ensuring timely and satisfactory outcomes.
- Build the systems that make partner success scale. Design and ship the tools, agents, dashboards, and automated workflows that turn one-off partner interactions into repeatable, self-serve experiences.
- Operate AI-first by default. Every repeatable part of your job, partner research, technical enablement prep, integration diagnostics, follow-ups, QBR analysis, should run through AI workflows you've designed.

## Requirements
- Thrive at the intersection of sales engineering, account management, and customer success.
- Have high EQ and high learning index, read the room, adapt your style, and quickly absorb technical and business complexity.
- Strong communicator who can keep many stakeholders aligned and focused, often through constant updates and over-communication on status and ownership.
- Energized by technical problem-solving, live demos, and translating support questions into growth conversations or business outcomes.
- See customer health and technical adoption not as endpoints but as the fuel for revenue expansion.
- Value collaboration and thrive in high-growth, fast-paced environments where priorities shift quickly.
- High degree of integrity and can work both collaboratively and independently in a remote WFH environment.
- Experience as Partner Manager, Technical Account Manager, Sales Engineer, Implementation Engineer, or Support Engineer.
- Comfortable with AI-first workflows, building tools/agents/pipelines/scripts to automate work.
- Deep understanding of APIs, integrations, and AI/ML technologies.

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