At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.
About LabelboxWe're the only company offering three integrated solutions for frontier AI development:
- Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
- Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models
- Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling
- High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.
- Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.
- Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.
- Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.
- Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.
We’re hiring a Forward Deployed Engineering Manager to lead the design, development, and delivery of reinforcement learning environments for agentic AI systems.
You’ll manage a team responsible for building sandboxed, reproducible environments—terminal-based workflows, browser automation, and computer-use simulations—that power both model training and human-in-the-loop evaluation. This is a hands-on leadership role where you’ll set technical direction, guide execution, and stay close to architecture and critical systems.
What You’ll Do- Lead, hire, and develop a high-performing team of Forward Deployed Engineers, setting a high bar for ownership, velocity, and technical quality
- Own the RL environment roadmap, aligning team execution with customer needs and evolving model capabilities
- Oversee development of sandboxed environments (terminal, browser, tool-augmented workspaces) that support deterministic execution and multi-step agent interaction
- Ensure reliability, observability, and data integrity through strong instrumentation (logging, trajectory capture, state snapshotting)
- Drive infrastructure excellence across containerization, sandboxing, CI/CD, automated testing, and monitoring
- Partner cross-functionally with data operations, product, and leading AI labs to define task design, evaluation protocols, and environment requirements
- Enable rapid prototyping and iteration, helping the team move from ambiguous requirements to production-ready systems quickly
- Stay close to the technical details—reviewing architecture, unblocking complex issues, and guiding design decisions
Required
- 5+ years of software engineering experience (Python)
- 2+ years of experience managing or leading engineers in fast-paced environments
- Strong experience with containerization and sandboxing (Docker, Firecracker, or similar)
- Solid understanding of reinforcement learning fundamentals (MDPs, reward design, episode structure, observation/action spaces)
- Background in infrastructure, developer tooling, or distributed systems
- Strong debugging skills and systems thinking across layered, containerized environments
- Ability to operate in ambiguity and translate loosely defined problems into clear execution plans
- Excellent communication and stakeholder management skills
Preferred
- Experience building or working with RL environments (Gym, PettingZoo) or agent benchmarks (SWE-bench, WebArena, OSWorld, TerminalBench)
- Familiarity with cloud infrastructure (GCP or AWS)
- Prior experience in AI/ML platforms, data companies, or research environments
- Contributions to open-source projects in RL, agents, or developer tooling
RL environment quality is a critical bottleneck in advancing agentic AI. Poorly designed or unreliable environments introduce noise into training loops and directly impact model performance.
In this role, you’ll lead the team building the environments that define how models learn—working across a range of cutting-edge projects with leading AI labs. Alignerr offers the speed and ownership of a startup with the scale and resources of Labelbox, giving you the opportunity to have outsized impact on the future of AI.
About AlignerrAlignerr is Labelbox’s human data organization, powering next-generation AI through high-quality training data, reinforcement learning environments, and evaluation systems. We partner directly with leading AI labs to build the data and infrastructure that push model capabilities forward.
Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.
- Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland
- Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility
- Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making
- Growth: Career advancement opportunities directly tied to your impact
- Vision: Be part of building the foundation for humanity's most transformative technology
We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs.
Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.
Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.
Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.
What We Do
Labelbox is the data factory for generative AI, providing the highest quality training data for frontier and task-specific models. Labelbox’s comprehensive platform combines on-demand labeling services with the industry-leading data labeling platform. The Boost labeling service is powered by the Alignerr community of highly-educated experts, who span all major languages and a diverse range of advanced subjects. They are available on-demand to rapidly generate new data for supervised fine-tuning, RLHF, and more. Labelbox’s software-first approach delivers unmatched control and transparency into the labeling process, leading to the generation of high-quality, consistent data at scale. Customers include Fortune 500 enterprises and leading AI labs, and Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins.
Why Work With Us
Labelboxers are driven to master their craft and build the best products for AI, which is quickly becoming one of the most significant technologies of our time. Join us in supporting our customers as they create AI breakthroughs.
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