Job description

Why AssemblyAI AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. We have a lab, and we also power our own models in our own proprietary inference environment. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for the best talent we can find to join a rapidly scaling team that's defining the future of the industry. We are one of the most capital-efficient AI companies on the planet - and are rapidly approaching $1M ARR per employee. We sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. We have thousands of customers building with us including the top startups and world renown enterprises, and are serving at tremendous scale: we process over 2 million hours of audio daily and handle more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven, the revenue is durable, and the growth trajectory is steep and getting steeper. We have a super flat culture and expect our employees' to be deeply intimate with the details at all levels. If you’ve ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build, this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you’ll actually know everyone’s name. About the Role We're hiring our first Senior GTM AI Engineer . This is a software engineering job inside the revenue org. You will build the pipelines, internal tools, and agents that decide which companies we go after, how we reach them, and what our sellers see when they open their laptop in the morning. Most of what a sales ops team used to do by hand is now something you can write software to do. Finding every company building voice AI before they contact us. Researching an account and drafting the first email. Watching product usage and telling an AE when a customer is about to expand or churn. Keeping the CRM clean without anyone filling in forms. You will build those systems, run them in production, and be judged on whether pipeline and revenue move. Your users are our AEs, SDRs, and GTM leaders. Your job is to make a small team perform like one three times its size. What You'll Do Write code every day. Python services, SQL models, scheduled jobs, and small internal apps are most of the job. You'll use Claude Code and similar tools to ship in days what used to take a quarter. Build agents that do the work: account research, lead qualification, outreach drafting, CRM hygiene, and usage monitoring. Design them, give them tools and data, evaluate their output, and keep them running. Turn product usage data in BigQuery and Looker into signals sellers act on: usage alerts, expansion triggers, and account health scores. Build the account targeting machine: sourcing, enrichment, dedupe, and ICP scoring, from raw data to a ranked list in a rep's queue. Integrate the systems the team already uses (our CRM, enrichment providers, outbound tools) so data moves between them without a human in the loop. Keep funnel data trustworthy: routing rules, field governance, and attribution. Prototype fast, measure what works, kill what doesn't, and work directly with Sales and Marketing leadership on what to build next. Document what you build so it keeps running without you. What You'll Need 4+ years as a software engineer, data engineer, or growth/GTM engineer, with time spent shipping systems that other people depend on. Strong Python and SQL. You have owned production automations end to end: APIs, webhooks, scheduled jobs, retries, error handling, and monitoring. Experience building with LLMs beyond a single prompt: multi-step agents, tool use, retrieval, and evaluation. You can tell whether an agent's output is good, and you know when a plain script is the better tool. AI-assisted development is how you work. You use Claude Code or similar tools daily, and you have the engineering judgment to review, test, and stand behind what they produce. Solid fundamentals: clean code, version control, code review, debugging, and a habit of thinking in systems. You do not need an engineering team to ship. Curiosity about how a sales org works. You don't need a RevOps background, but you need to care about how deals get found and closed, and be willing to learn our CRM and the tools around it quickly. A builder's mindset with an operator's judgment: you scope for business impact, ship iteratively, and measure results in pipeline and revenue. Low ego, high ownership, and comfort being the single-threaded owner of an entire domain. Nice to Have Hands-on Salesforce or other CRM work at the object and API level, or experience with enrichment and outbound tools like Clay. dbt, BigQuery, and Looker, or an equivalent warehouse and BI stack. Time at a developer-facing or API-first company, or selling to technical buyers. You've been the first engineer in a sales or growth org and built the function from scratch. Pay Transparency: AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage, and industry, and are one part of many compensation, benefit, and other reward opportunities we provide. There are many factors that go into salary determinations, including relevant experience, skill level, qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. The provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range which will be communicated to candidates throughout the interview process. Salary range: $160,000 to $220,000 Using AI in your interview If you’re selected for an interview, please read our Candidate AI Guidance . It explains how you can use AI at each stage of our process, from your application and take-home to the interviews themselves. GDPR privacy notice If you’re applying from the EU or UK, please review our Job Applicant Privacy Notice before applying. Keep exploring AssemblyAI Transcribe: Speech-to-Text | Streaming Speech-to-Text Understand: Speech Understanding | LLM Gateway Interact: Voice Agent API | Dictation API Try our models in the Playground See how 50+ LLMs rank on real voice tasks: Voice Standard Bench Watch us on YouTube

Requirements

Must-haves

Why AssemblyAI
Your users are our AEs, SDRs, and GTM leaders. Your job is to make a small team perform like one three times its size.
Write code every day. Python services, SQL models, scheduled jobs, and small internal apps are most of the job. You'll use Claude Code and similar tools to ship in days what used to take a quarter.
Build agents that do the work: account research, lead qualification, outreach drafting, CRM hygiene, and usage monitoring. Design them, give them tools and data, evaluate their output, and keep them running.
Turn product usage data in BigQuery and Looker into signals sellers act on: usage alerts, expansion triggers, and account health scores.
Build the account targeting machine: sourcing, enrichment, dedupe, and ICP scoring, from raw data to a ranked list in a rep's queue.
Integrate the systems the team already uses (our CRM, enrichment providers, outbound tools) so data moves between them without a human in the loop.
Keep funnel data trustworthy: routing rules, field governance, and attribution.
Prototype fast, measure what works, kill what doesn't, and work directly with Sales and Marketing leadership on what to build next.
Document what you build so it keeps running without you.
What You'll Need
4+ years as a software engineer, data engineer, or growth/GTM engineer, with time spent shipping systems that other people depend on.
Strong Python and SQL. You have owned production automations end to end: APIs, webhooks, scheduled jobs, retries, error handling, and monitoring.
Experience building with LLMs beyond a single prompt: multi-step agents, tool use, retrieval, and evaluation. You can tell whether an agent's output is good, and you know when a plain script is the better tool.
AI-assisted development is how you work. You use Claude Code or similar tools daily, and you have the engineering judgment to review, test, and stand behind what they produce.
Solid fundamentals: clean code, version control, code review, debugging, and a habit of thinking in systems. You do not need an engineering team to ship.
Curiosity about how a sales org works. You don't need a RevOps background, but you need to care about how deals get found and closed, and be willing to learn our CRM and the tools around it quickly.
A builder's mindset with an operator's judgment: you scope for business impact, ship iteratively, and measure results in pipeline and revenue.
Low ego, high ownership, and comfort being the single-threaded owner of an entire domain.

Nice-to-haves

Hands-on Salesforce or other CRM work at the object and API level, or experience with enrichment and outbound tools like Clay.
dbt, BigQuery, and Looker, or an equivalent warehouse and BI stack.
Time at a developer-facing or API-first company, or selling to technical buyers.
You've been the first engineer in a sales or growth org and built the function from scratch.

Application prep

Use the role’s language and application details while tailoring your materials.

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