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Sobre esta vaga de Senior GTM AI Engineer na AssemblyAI

AssemblyAI · Remoto · Remote - North America

Why AssemblyAI

AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. 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 folks truly excited to join a small team and help define the future of the industry.

We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $600K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything.

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.

We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!

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

AI to Interview:

If you’re selected for an interview, please review this resource to better understand how AssemblyAI approaches the use of AI in our interview process.

GDPR privacy notice:

Candidates from the EU should review this job applicant privacy notice before applying. 

Keep Exploring AssemblyAI:

Speech-to-text | Streaming speech-to-text | Speech Understanding | LLM Gateway
Try the Playground
Our $50M Series C fundraise
Check us out on YouTube!

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Como este salário de AI Engineer se compara

Esta vaga paga $190,000/yr — abaixo da faixa típica para vagas de AI Engineer.

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Sobre a AssemblyAI

About AssemblyAI

AssemblyAI builds the best-in-class Speech AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences—from voice agents and meeting assistants to contact centers and medical scribes. Companies like Zoom, Granola, Fireflies, Cluely, and Calabrio rely on AssemblyAI to ship production-ready voice AI.


We're at an inflection point in Speech AI. We released Universal-Streaming in mid-2025, and it has quickly earned its place as the model offering the best accuracy-latency-cost tradeoff on the market. The adoption has been significant: we now process ~1.5M streaming hours per week, with 25x usage growth in the last six months alone. Our research team drives these advances and ships with relentless velocity. Since releasing Universal-Streaming, we've already launched keyterms prompting feature and multilingual support—with more significant improvements on the roadmap.


We've raised $115M+ from Accel, Insight Partners, Y Combinator's AI Fund, Patrick and John Collison, Nat Friedman, and Daniel Gross. We're a remote team building one of the next great AI companies—and we're looking for people who will shape its future.

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