Forward Deployed Engineer (FDE)

Location

San Mateo, CA

Fully onsite, 5 days per week, Monday–Friday.

Company Stage of Funding

Series A

The company has raised $70 million in Series A funding, backed by leading venture investors. Revenue is strong and growing quickly.

Office Type

On-site — 5 days per week

Salary

$230,000–$310,000 Base

Equity

Competitive Equity

Visa

Open to visa transfers, including H-1B and OPT transfers.

Employment Type

Full-time

Company Description

This venture-backed company is building the data engine for physical AI, delivering high-quality teleoperation and robotics training data to frontier AI labs and leading humanoid robotics companies worldwide.

The company has raised $70 million in Series A funding from prominent investors, including Thrive, Andreessen Horowitz, and Spark Capital. Its founders have backgrounds in Berkeley robotics research and experience at leading robotics companies. With strong, growing revenue and increasing demand from major customers, the company is scaling its customer delivery and engineering capabilities.

The company is looking for a Forward Deployed Engineer (FDE) to own end-to-end technical delivery for its most strategic enterprise customers in the robotics and frontier AI space. This is a founding FDE role, offering the opportunity to establish the forward-deployed engineering function and shape how the company serves its largest accounts.

The ideal candidate combines strong software engineering skills with excellent customer communication. They should be able to understand complex technical systems, independently troubleshoot customer issues, manage data delivery, and translate technical concepts into clear, actionable explanations.

This is not a traditional sales engineering role. The company needs a hands-on engineer who can write production-quality code, solve technical problems independently, and build trust with sophisticated robotics and AI customers.

What You Will Do

1. Own End-to-End Customer Delivery

• Own technical delivery for a portfolio of strategic customers, including leading robotics companies and frontier AI organizations.

• Understand the complete data pipeline, from customer requirements and data collection through quality assurance and final delivery.

• Scope customer requirements and translate them into concrete technical execution plans.

• Ensure data quality and verify deliverables before they are shipped to customers.

• Identify delivery blockers, troubleshoot issues, and drive resolution independently.

• Coordinate across internal teams to ensure customer requirements are understood and delivery commitments are met.

• Take responsibility for the quality, accuracy, and timeliness of customer deliverables.

• Build a deep understanding of each customer's technical requirements and how delivered data affects their model performance.

• Manage multiple customer engagements while maintaining high standards of delivery and communication.

2. Troubleshoot Technical Customer Issues

• Serve as the first technical point of contact for assigned customer accounts.

• Triage customer questions, investigate technical issues, and resolve most problems without escalating to other engineers.

• Use strong coding and debugging skills to identify root causes and implement practical solutions.

• Understand the underlying data pipeline and related technical systems well enough to diagnose issues end-to-end.

• Communicate technical limitations, delivery risks, and timelines clearly to customers.

• Set realistic expectations and proactively communicate when an issue may affect delivery.

• Distinguish between issues that can be resolved independently and those requiring additional engineering support.

• Develop a structured approach to recurring customer issues, reducing repeated troubleshooting effort.

• Maintain customer confidence through timely responses, clear explanations, and reliable execution.

3. Work Directly With Robotics & Frontier AI Customers

• Build trusted technical relationships with sophisticated customers in the robotics and AI ecosystem.

• Represent the company's technical capabilities in customer conversations and implementation discussions.

• Translate complex technical concepts into language that customers can understand and act on.

• Understand how customer requirements connect to robotics workflows, AI model development, and training data quality.

• Gather technical feedback and clarify requirements before committing to implementation or delivery timelines.

• Collaborate with customer engineering teams to resolve integration and data-related challenges.

• Proactively identify risks, communicate tradeoffs, and ensure customers feel informed and supported.

• Balance technical depth with customer empathy and strong relationship management.

• Help customers understand how the delivered data supports their broader AI and robotics objectives.

4. Improve Data Pipelines & Delivery Processes

• Identify recurring customer issues, operational bottlenecks, and data delivery pain points.

• Turn customer feedback into concrete improvements to internal tools, software, and data pipelines.

• Write code to automate repetitive work and improve delivery reliability.

• Develop reusable solutions and playbooks for common technical and customer-facing scenarios.

• Improve data validation, quality assurance, and pre-delivery checks.

• Work with engineering and operations teams to make delivery processes more scalable.

• Document solutions and establish repeatable practices that reduce dependence on individual engineers.

• Identify opportunities to improve the reliability, efficiency, and consistency of customer delivery.

• Use hands-on engineering to solve immediate customer problems while contributing to long-term platform improvements.

5. Build the Forward-Deployed Engineering Function

• Help define the company's forward-deployed engineering approach from the ground up.

• Establish repeatable processes for customer onboarding, technical delivery, troubleshooting, and account support.

• Develop playbooks for common customer requirements, integration challenges, and delivery workflows.

• Help determine how technical ownership should be structured across strategic accounts.

• As the role evolves, lead platform-integration engagements for enterprise customers.

• Support the development of model fine-tuning and evaluation services for enterprise customers.

• Identify patterns across customer engagements and translate them into scalable engineering capabilities.

• Work in a high-ownership environment where processes are still being established.

• Help shape the future of the forward-deployed team as customer demand grows.

Ideal Candidate Background

Experience Requirements

• Typically 5–8 years of experience as a customer-facing Software Engineer or Forward Deployed Engineer.

• Strong candidates with 3+ years of experience at highly technical companies such as Palantir or Snowflake may also be considered.

• Experience in customer-facing engineering at a highly technical enterprise or S-tier technology company is a dealbreaker requirement.

• Demonstrated ability to combine hands-on software engineering with direct customer engagement.

• Experience independently troubleshooting and resolving technical customer issues.

• Experience working with sophisticated technical customers and complex product requirements.

• Strong production coding and problem-solving skills.

• Experience taking ownership of technical delivery from scoping through implementation and resolution.

• Founding engineer or startup founder experience is a plus.

• Robotics or embodied AI experience is a plus.

• Ability to work fully onsite in San Mateo, CA, 5 days per week.

Technical Requirements

• Strong software engineering fundamentals and production coding ability.

• Python preferred.

• Ability to independently debug, troubleshoot, and resolve technical issues.

• Experience understanding and working across data pipelines.

• Ability to scope technical requirements and translate them into practical implementations.

• Strong problem-solving skills when dealing with ambiguous technical issues.

• Ability to understand complex technical systems and identify root causes.

• Experience building or maintaining reliable software used in customer-facing environments.

• Ability to improve existing workflows through code, automation, and reusable tooling.

• Comfort working directly with customer engineering teams.

• Familiarity with data formats and technologies such as MCAP and HDF5 is relevant to the role's technical environment.

• Ability to learn unfamiliar systems and customer workflows quickly.

Customer-Facing Engineering Requirements

• Experience in a customer-facing engineering role, rather than solely internal software development.

• Ability to independently own technical customer issues and drive them to resolution.

• Strong communication skills with technical stakeholders.

• Ability to explain complex technical concepts clearly and accurately.

• Experience gathering requirements and translating customer needs into technical work.

• Ability to manage customer expectations around scope, timelines, and technical limitations.

• Strong collaboration skills across customer-facing and internal engineering teams.

• Ability to prioritize multiple customer issues and delivery commitments.

• Confidence representing technical capabilities to sophisticated enterprise customers.

• Ability to build customer trust through technical depth, reliability, and clear communication.

Data Pipelines & Physical AI Requirements

• Ability to understand data pipelines and end-to-end delivery workflows.

• Experience with data quality checks, validation, and quality assurance.

• Ability to investigate data-related issues and determine their root causes.

• Understanding of how data quality affects downstream applications and model performance.

• Experience working with complex technical data or integration workflows.

• Familiarity with Python-based data processing.

• Familiarity with MCAP, HDF5, robotics, or AI/ML is beneficial.

• Experience with robotics or embodied AI is a plus, but strong customer-facing engineering and coding skills remain central.

• Ability to convert recurring delivery challenges into scalable technical improvements.

Startup & Ownership Requirements

• Comfortable working in a fast-growing, high-demand startup environment.

• Able to work independently with limited direction.

• Proactive in identifying and resolving technical problems.

• Comfortable operating in ambiguity and building processes from the ground up.

• Able to balance immediate customer needs with longer-term engineering improvements.

• Strong sense of ownership over customer outcomes and technical delivery.

• Willing to help define the forward-deployed engineering function.

• Able to identify patterns across customer accounts and build reusable solutions.

• Founding engineer or startup founder experience is a plus.

Soft Skills

• Excellent customer communication and relationship management.

• Strong technical translation skills: able to explain complex systems in accessible language.

• High agency and independent problem-solving ability.

• Strong collaboration across engineering, operations, and customer teams.

• Clear communication about blockers, risks, and delivery timelines.

• Ability to remain composed and effective when customers face urgent technical issues.

• Practical, solution-oriented mindset.

• Strong organizational skills and attention to detail.

• Ability to prioritize multiple customer needs without compromising delivery quality.

• Comfort with ambiguity and changing priorities.

• Customer empathy combined with strong technical judgment.

• Proactive follow-through and accountability.

Nice-to-Have Qualifications

• Experience as a founding engineer or startup founder.

• Experience at companies such as Palantir or Snowflake.

• Experience in robotics, embodied AI, or physical AI.

• Familiarity with MCAP and HDF5.

• Experience supporting frontier AI labs or humanoid robotics companies.

• Experience with teleoperation data, robotics training data, or data quality workflows.

• Experience with platform integrations for enterprise customers.

• Experience supporting model fine-tuning or evaluation services.

• Experience building customer delivery playbooks and scalable technical processes.

• Experience helping establish a forward-deployed engineering function.

Compensation & Benefits

• Base salary: $230,000–$310,000.

• Equity: Competitive equity package.

• Visa: H-1B and OPT transfers supported.

• Work model: Fully onsite in San Mateo, CA, 5 days per week.

• Employment: Full-time.

• Opportunity to work directly with leading robotics and frontier AI companies.

• Founding FDE opportunity with end-to-end ownership of strategic customer accounts.

• Opportunity to shape customer delivery and forward-deployed engineering processes.

• Hands-on technical work spanning software engineering, data pipelines, and robotics-related workflows.

• Opportunity to turn customer challenges into scalable product and platform improvements.

Why Join

• Work at the intersection of AI and robotics: Help deliver high-quality data that supports the development of physical AI systems.

• Own strategic customer relationships: Become the technical owner for sophisticated enterprise customers and leading robotics companies.

• Shape a founding function: Help define how forward-deployed engineering operates as the company scales.

• Stay hands-on technically: Solve real customer problems through coding, debugging, and engineering.

• Build scalable systems: Turn recurring customer pain points into reusable tools, playbooks, and pipeline improvements.

• Work with high-profile customers: Collaborate with companies building advanced AI and robotics systems.

• Take end-to-end ownership: Manage technical delivery, customer communication, quality assurance, and issue resolution.

• Grow with a scaling company: Join a well-funded Series A business with strong and growing revenue.