Forward Deployed Engineering Manager

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 Labelbox We'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 Why Join Us 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. The role The FDE Manager leads and grows the team of Forward Deployed Engineers who own the high-level technical side of our customer data programs. FDEs scope tasks, design the pipelines and measurement that turn a customer's goal into a training signal, write the instructions that guide Alignerrs, and work out what each customer actually needs from their data. The FDE Manager owns the people who do that work — their craft, their growth, and how they're deployed across domains and customers — and is accountable for the technical quality and consistency of what the team produces. This role sits at the intersection of people leadership, technical depth, and delivery quality. The FDE Manager must understand the technical substance of our projects well enough to coach on scoping and pipeline design, pressure-test instructions, judge whether a project's data will genuinely move the customer's model, and raise the bar on measuring quality early rather than late. It's a player-coach role: you lead people, but you stay close enough to the work to set and defend the craft bar yourself. The FDE Manager reports to the Services lead and partners closely with the SPL Manager, Deployment Leads, and General Managers. A core part of the role is keeping FDEs at the right altitude — focused on higher-level technical and customer-facing work — and actively handing the day-to-day running of projects to the SPLs and Pod Leads, so the team's most expensive technical talent is never absorbed into project operations. The FDE Manager also owns FDE onboarding and is the steward of the FDE career path, which runs from FDE to FDE 2 to FDE Manager, with branches toward the Forward Deployed Researcher (FDR) track and, in time, toward General Manager. What You'll Do Lead the FDE team end-to-end: hire, coach, manage performance, and develop careers across the FDE track and toward FDR or GM. Own the supply side of FDE staffing: commit FDEs to the staffing cadence and match them to projects by skill and development need, balancing each FDE's preferred vertical with where the work is, and staffing to the phase of a project rather than parking people for its full length. Set and uphold the craft bar: sharp task scoping, sound pipeline and measurement design (including the LLM-as-judge and quality instrumentation that surface problems early), clear instruction writing, and compelling customer-facing presentation of findings. Protect FDE focus: keep day-to-day project operations with the SPLs and Pod Leads, and keep FDEs on scoping, technical depth, and what the customer needs from the data. Own FDE onboarding and the bar that certifies a new FDE as ready to be staffed: define which projects are eligible to onboard on, maintain the instruction and Loom repository, and run the onboarding program — including the core exercise (read a past project's instructions, explain them back, and write a new version in the repo). Drive reuse and leverage: build the templates, tooling, and playbooks that stop FDEs rebuilding pipelines and instructions from scratch each project, so the team's capacity compounds as we scale. Ensure FDEs work hand-in-glove with FDRs on research, efficacy, and customer needs, and partner with whoever owns quality sign-off so quality is caught in flight, not at delivery. Partner with the SPL Manager, Deployment Leads, and GMs on staffing, delivery, and alignment with customer objectives. Step in on escalations when a pipeline, delivery, or customer relationship is at risk. Maintain a clear, live view of team capacity, utilization, and bench across active projects. What You'll Own The capability and craft bar of the FDE team. How quickly and consistently new FDEs reach a staffable standard. Healthy deployment — the right FDEs on the right projects, at the right altitude and utilization. A growing bench of FDEs developing toward FDR and future leadership. What We're Looking For A strong forward-deployed / FDE background, or significant experience managing technical or delivery people — and readiness to be a hands-on, player-coach manager. Strong technical fluency in our domain: enough depth in frontier-data work, RL environments, data pipelines, and quality/evaluation to coach credibly on scoping, pipelines, judge design, and data quality. Excellent judgment on what makes data genuinely useful to a customer — how to translate ambiguous requirements into clear plans, and how to tell whether data will actually move a model. A track record of developing people and giving direct, useful feedback. A high bar for quality paired with the ability to deliver against ambitious timelines. Comfort operating in ambiguous, fast-scaling environments where the processes are still being built. The ability to manage multiple people and projects at once without losing attention to detail. Nice to Have Direct experience with RLHF, reinforcement-learning environments, evaluation/benchmark work, or LLM-as-judge systems. Experience working with forward-deployed engineers, solutions engineers, or implementation teams. Experience building onboarding programs, instruction systems, or training content. Experience scaling a team and its operating processes in a high-growth environment. What Success Looks Like In your first several months, you'll take ownership of the FDE team, raise the bar on scoping, pipeline, and instruction quality, and get onboarding running smoothly — eligible projects defined, the instruction and Loom repository in good shape, and new FDEs reaching a staffable standard faster and more consistently. You'll build strong working relationships with the SPL Manager, Deployment Leads, and GMs, keep FDEs well-deployed and at the right altitude, and become the person the team relies on for craft and career growth. Over time, you'll define how FDEs work at scale: the templates, tooling, and playbooks that let the team produce more without rebuilding from scratch, a measurement-and-quality craft bar that surfaces problems early, and a pipeline of FDEs growing into FDRs and future leaders. 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. Annual base salary range

$190,000 - $250,000 USD

Life at Labelbox Location : Join our dedicated tech hub in San Francisco Work Style : Hybrid model with 3 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 Our Vision 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. #J-18808-Ljbffr Labelbox Inc.