Forward Deployed Engineer (Physical AI)

Forward Deployed Engineer | Physical AI
Location: San Francisco, CA
Work model: Full-time, five days per week in office
Compensation: $150K to $200K base plus meaningful equity

The Company
My client is a 10-person, Greylock-backed AI startup building a scientific intelligence platform for the physical world.

They work with scientists and engineers across semiconductors, batteries, advanced materials, chemicals, aerospace, and manufacturing. These industries generate enormous amounts of valuable data, but it is often fragmented across spreadsheets, sensor logs, lab notebooks, reports, vendor documents, and experimental systems.

The company is building a unified intelligence layer for this information, powering specialized AI agents that help automate difficult workflows such as failure analysis, experimental design, and manufacturing optimization.

They have raised a $7M seed round from Greylock and other leading investors. The founders are Harvard computer science graduates with experience at SpaceX, Warp, and the MIT-IBM Watson AI Lab. The broader team includes engineers from Applied Intuition, Glean, Jane Street, Verkada, and Meta.

The Role
This is a hands-on engineering role for someone who wants to combine software development, AI, product thinking, and direct customer work.

You will work firsthand with scientists and engineers in labs, R&D facilities, and manufacturing environments. You will learn how they operate, identify the real problem behind their requests, and build software that improves how physical technologies are researched, tested, and manufactured.

You will own projects from initial customer conversations through technical design, implementation, deployment, and iteration. Problems will often be ambiguous, and customers may not know how to translate their scientific needs into software requirements.

Responsibilities
Work directly with scientists and engineers to understand complex R&D and manufacturing workflows
Translate ambiguous customer problems into clear technical solutions
Build AI agents, product features, integrations, internal tools, and data pipelines
Connect fragmented scientific data across lab systems, sensor logs, spreadsheets, reports, literature, and patents
Prototype quickly and iterate based on feedback from real users
Own deployments from initial discovery through production
Turn successful customer projects into reusable product capabilities
Partner closely with the founders and the ML, product, and infrastructure teams
Travel to customer sites when needed

Ideal Background
Approximately 1 to 5 years of professional software engineering experience
Strong software development and problem-solving fundamentals
Experience shipping production backend, full-stack, data, or AI systems
Practical familiarity with LLMs, agents, retrieval systems, multimodal AI, or machine learning
Strong communication skills and genuine interest in working directly with customers
Ability to operate independently without detailed requirements or structured tickets
Interest in physical industries, scientific research, robotics, hardware, or manufacturing
Willingness to work five days per week from the San Francisco office
Comfort traveling to customer facilities

Relevant Candidate Profiles
Strong candidates could come from:
Forward deployed or customer-facing engineering
Early-stage product or backend engineering
Applied AI or machine learning engineering
Robotics, autonomy, aerospace, semiconductors, batteries, or industrial software
Technical founder or founding engineer backgrounds
Computer science, electrical engineering, physics, materials science, mechanical engineering, chemical engineering, or related disciplines
A traditional computer science background is not required. Candidates from physical science or engineering disciplines can be highly compelling if they have strong software-building experience.

Technology
The current stack includes:
Rust
AWS
Kubernetes
Terraform
React
Next.js
Foundation models, AI agents, multimodal systems, retrieval, and scientific data integrations
Experience with every technology is not required. The company values engineers who learn quickly and choose the right tools for the problem.

Why Join
Apply AI to difficult problems in science, engineering, and manufacturing
Work directly with the people developing semiconductors, batteries, materials, and other frontier technologies
Own meaningful customer and product outcomes from day one
Help define the Forward Deployed Engineering function at a 10-person company
Work with an exceptionally technical team backed by leading AI and venture investors
Receive meaningful ownership at an early stage


Show more Show less