Forward Deployed Engineer FDE

XDOF; San Mateo; On-site; PHP 800,000 - 1,200,000; Full time

Job summary

XDOF is seeking a founding Forward Deployed Engineer in the Philippines to own delivery for strategic customers, translating needs into concrete data collection and annotation specs and ensuring their models improve with the shipped data.

You will be the main technical owner for accounts, interfacing between customer delivery and platform development, guiding early-stage motion as the company scales.

Qualifications

• 5+ years of engineering experience, ideally including customer-facing work.
• Strong production coding in Python with experience shipping data pipelines or infrastructure.
• High agency and comfort with ambiguity: you drive customer outcomes.
• Excellent communication and low ego: you explain tradeoffs to engineers and executives.

Responsibilities

• Own end-to-end delivery for a set of strategic customers, including scope, sequencing, QA, and blockers.
• Be the first technical responder for accounts; manage timelines and evolving data products.
• Represent XDOF's technical depth to customers while protecting proprietary methods.
• Turn recurring needs into input for data-engine, pipeline, and annotation roadmaps; codify learnings.
• As the role matures, lead platform-integration engagements and model fine-tuning services.

Skills

Python

Data pipelines

Customer facing

Communication

Ambiguity management

Tools

MCAP

HDF5

Job description

Job Description

About XDOF

XDOF is the data engine for embodied intelligence. We help the world's leading robotics and foundation-model labs unlock general-purpose robots by delivering the highest-quality teleoperation, on-embodiment, and egocentric data and paired with our own hardware ecosystem and a model fine-tuning loop that closes the loop on data quality. We recently emerged from stealth and are scaling our customer base of frontier AI and humanoid companies quickly.

About The Role

We're hiring our founding Forward Deployed Engineers. You'll embed with our most strategic customers and own their success end-to-end, from translating their model and data needs into concrete collection / annotation / delivery specs, to making sure the data we ship actually moves their model performance.

This is a critical role that today, our founders and core engineers absorb directly. As an FDE, you'll be the single technical owner for a portfolio of accounts, sitting at the intersection of customer delivery and core platform development, and you'll help define our forward-deployed motion as we grow.

What You'll Do

• Own end-to-end delivery for a set of strategic customers: scope requirements, sequence delivery, QA before shipping, and clear blockers.
• Be the first technical responder for your accounts: triage questions, manage expectations on timelines and on still-maturing data products, and elevate only what genuinely needs it.
• Represent XDOF's technical depth to sophisticated customers while protecting proprietary methodology
• Close the loop: turn recurring customer needs and delivery pain into concrete input for our data-engine, pipeline, and annotation roadmaps, and codify what works into reusable playbooks.
• Grow the motion: as the role matures, lead platform-integration engagements and model fine-tuning / evaluation services for enterprise customers.

What We're Looking For

• 5+ years of engineering experience, ideally including customer-facing or forward-deployed work.
• Founding-engineer profile, strongly preferred: you've owned many things at once and solved hard problems without a playbook, and you want to talk to customers.
• Strong production coding (Python preferred), with real experience shipping and operating data pipelines or infrastructure.
• High agency and comfort with ambiguity: you drive customer outcomes rather than wait for a spec.
• Excellent communication and low ego: you can run discovery, push back respectfully on unrealistic asks, and explain hard tradeoffs to both engineers and executives.

Nice to have

• Background in robotics, embodied AI, autonomy, or ML data infrastructure.
• Familiarity with robot-learning data (teleoperation, egocentric, VLA / robot foundation models) and formats like MCAP, HDF5, etc.
• Forward-deployed or solutions experience at an enterprise or frontier-AI company.

Requirements: