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Full-Stack Engineer (Backend Leaning) – Studio

AI Summary
ElevenLabs is hiring a backend-leaning full-stack engineer for Studio, its creator-focused video production product. The role will own a greenfield workflow that transforms completed projects into localized video outputs with dubbing, translated captions, and multiple aspect ratios. The engineer will define requirements through RFCs, validate complex data structures with the team lead, and deliver the system from inception through launch. Success requires strong backend system design, product judgment, autonomous execution, and familiarity with enterprise concerns such as account management and usage reporting.
Remote from
UK, USA, Poland+1 more, Bulgaria
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
4 Dec 2026
Listing views
21
Application actions
2
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Opportunity details

About this role.

About ElevenLabs

ElevenLabs is an AI research and product company transforming how we interact with technology.

We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses – from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world’s most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We’ve raised $781M in funding and our last valuation was $22B – multiples of 11, always.

We have expanded from voice into three main platforms:

  • ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.

  • ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.

  • ElevenAPI gives developers access to our leading AI audio foundational models.

Everything we do is the result of the creativity and commitment of our team – builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.

How we work

  • High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.

  • Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.

  • AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.

  • Excellence everywhere: Everything we do should match the quality of our AI models.

  • Global team: We prioritize your talent, not your location.

What we offer

  • Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.

  • Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact – beyond your immediate role and responsibilities.

  • Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.

  • Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.

  • Annual team offsite: Each year, we bring your entire team together in a new location – past offsites have included Croatia, Italy and Cancún

  • Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.

About the role
Studio is where creators build and finish video on ElevenLabs, powered by our generative graph engine, Flows. You’ll own our “produce once, distribute everywhere” workflow. It takes a finished Studio project and runs it through our dubbing pipeline to produce it in many languages and aspect ratios, with auto-translated captions. Today that means duplicating and rebuilding projects by hand.
This work is entirely greenfield: the specs aren’t written yet. You’ll shape them through written proposals (RFCs), pressure-test data structures with the team lead, and carry the project from first draft to launch.
You’re a strong backend generalist who is good with complex data structures and has the product instincts to decide what’s worth building.

Requirements

  • Strong backend generalist who has designed and shipped complex, data-heavy systems end to end.

  • Comfortable with enterprise-grade concerns such as usage reporting and accounts.

  • Evidence of product ownership: side projects, open source, or work in a product-facing context.

  • Has taken projects from inception to launch with little hand-holding.

Bonus: experience with media or video-processing pipelines (helpful, not required)

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThis is a greenfield ownership role involving complex, data-heavy backend systems and ambiguous product specifications. The engineer must independently make architectural and product decisions while operating in a high-velocity environment.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Highly competitive
$185,000
US market range (per year)$150k–$220k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer base salary was disclosed. The yearly cadence and USD market estimate are inferred for a senior backend-leaning full-stack engineering role in the stated hiring markets; actual compensation may vary by country, level, and equity structure.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a workflow that creates localized versions of a completed Studio project across languages and aspect ratios?

I would model the source project as an immutable versioned input and create explicit derivative-job records for each language and format combination. Jobs would move through an asynchronous, idempotent orchestration pipeline with durable state, retries, observability, and clear links to generated assets. This enables partial reprocessing when a caption, translation, or rendering step changes without rebuilding every output.

Describe how you approach a greenfield project when the specifications are not yet defined.

I begin by identifying the user outcome, operational constraints, and irreversible architectural decisions. I write a concise RFC that compares viable approaches, proposes an initial data model and API boundaries, and highlights open questions. After gathering feedback, I deliver the smallest valuable vertical slice, measure its behavior, and iterate with stakeholders.

What design considerations would you prioritize for a data-heavy system that manages projects, localized variants, and media assets?

I would prioritize clear entity ownership, versioning, referential integrity, and query patterns that support both operational workflows and reporting. Large media files should be stored separately from transactional metadata, with stable asset references and lifecycle policies. I would also plan for auditability, access control, quotas, and backfills from the start.

How would you ensure reliable usage reporting for enterprise customers?

I would emit immutable, structured usage events at the point where billable or reportable actions occur, using idempotency keys and a durable event pipeline. Aggregations should be reproducible from source events, reconciled regularly, and separated from the real-time product path where possible. I would expose transparent reporting definitions and monitor for event loss, duplication, and processing lag.

Tell us about a time you had to balance a technically elegant solution against shipping product value quickly.

I would explain the user impact, the risks of overbuilding, and the smallest architecture that preserved future options. A strong approach is to ship a well-instrumented initial implementation behind clear interfaces, document known constraints, and define decision points for later investment. This delivers value promptly without accumulating hidden, irreversible technical debt.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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