Title: Founding Software Engineer

Location: Palo Alto, CA (Hybrid)

Reporting Structure: 

Company Description

Our client is building the infrastructure layer for Physical AI and Spatial Intelligence in the real world. Their systems turn massive, continuously changing streams of spatial and operational data into live, queryable digital representations that machines and people can act on. The backend is not a support function: it is a core part of the product and a hard technical problem in its own right.

Quick facts:

• Founded in 2024
• Raised $1.7M pre-seed
• Head of AI is a visiting Google DeepMind scholar and robotics professor

Role Description



They are hiring a Founding Software Engineer to help take this platform from zero to one. You will build across the product: cloud infrastructure, backend services, APIs, authentication, storage, databases, and the frontend experiences that make these capabilities useful to customers.

This is a generalist role with a strong backend emphasis, approximately 75% backend and infrastructure, and 25% frontend. You should be comfortable designing a system, deploying it, building the interface around it, and working directly with users to understand what needs to improve.

You will help turn ambitious research and robotics capabilities into a dependable software product, making foundational technical decisions while shipping working software.

Responsibilities

Build the systems that make us fast, trustworthy, and programmable - from bytes in memory to a production API used by critical real-world applications.

Depending on your background, this may include:

• Backend and infrastructure (approximately 75%)
• Cloud infrastructure: Build and operate infrastructure across cloud providers such as AWS, GCP, and Azure. Use infrastructure as code, automated deployments, and clear environment boundaries to support development, production, and customer deployments.
• APIs and services: Design serverless APIs, containerized services, background jobs, and event-driven workflows. Choose the right execution model for each workload, balancing latency, throughput, reliability, and cost.
• Authentication and authorization: Implement user and machine identities, API keys, OAuth/OIDC, role-based access, tenant isolation, and secure secrets management. Make it straightforward for customers to connect their teams, applications, and devices.
• Storage and databases: Select and integrate relational databases, object storage, caches, and specialized data systems where needed. Own data modeling, indexing, schema migrations, retention, backups, and recovery.
• Robotics and spatial data pipelines: Build reliable ingestion and processing for sensor streams, 3D data, telemetry, and model outputs. Connect edge systems to cloud services, accounting for intermittent connectivity, retries, backpressure, and evolving data formats.
• Product foundations: Build the services behind organizations, projects, device management, configuration, usage tracking, and customer onboarding. Integrate research and ML components into APIs and workflows customers can use.
• Production readiness: Establish CI/CD, practical automated testing, observability, security controls, and incident diagnostics. Identify performance bottlenecks and improve reliability and cloud costs as usage grows.
• Frontend and product (approximately 25%)
• Build customer-facing web applications and internal tools for onboarding, configuring integrations, managing access, and monitoring systems.
• Create interfaces for exploring spatial data, inspecting processing results, and understanding device or service health.
• Own features from API to interface, including loading states, errors, permissions, and responsive behavior. Work directly with users and the team to turn complex technical capabilities into clear workflows.
• As a founding engineer
• Help decide what to build, what to buy, and where custom engineering creates meaningful product value.
• Turn ambiguous requirements into focused milestones, ship the smallest useful solution, and strengthen it as real usage reveals what matters.
• Work closely with research, robotics, and product teammates to move prototypes into production.
• Shape engineering practices, document consequential decisions, and help recruit the early team.

Is this you?

They care more about exceptional problem-solving ability and demonstrated systems depth than credentials or a specific career path. You are the kind of engineer who can move between an algorithm, a profiler trace, a distributed failure mode, and a product decision without losing rigor.

• Experience shipping software end to end, with strong backend skills and enough frontend fluency to independently deliver a complete customer workflow.
• Strong programming ability in a backend language such as Python, TypeScript, Go, or Rust, and practical experience with React, TypeScript, or a comparable frontend stack.
• Hands-on experience deploying and operating cloud services, including serverless functions, containers, networking, identity and access management, and infrastructure as code.
• Sound judgment around API design, authentication, database schemas, storage, asynchronous processing, and security boundaries.
• The ability to debug across the stack—from a confusing UI interaction to a slow query, failed deployment, or unreliable data pipeline.
• Comfort choosing established tools, understanding their limits, and building custom components when the problem warrants it.
• Founder-level ownership: you can work through ambiguity, communicate tradeoffs, and take responsibility for software after it ships.

You do not need to have used every technology listed here. They are looking for technical range, depth in backend engineering, and the ability to learn quickly.

Especially Relevant Experience

• Taking an early-stage product from prototype to production and supporting its first customers.
• Robotics, edge computing, IoT, geospatial systems, 3D visualization, or high-volume sensor data.
• Deployments across multiple cloud providers, customer cloud accounts, or hybrid environments.
• Integrating ML inference, GPU workloads, streaming systems, or developer tools into a production product.

Robotics experience is a plus, but it is not required. Show us a product, platform, open-source contribution, or technically ambitious project you helped bring to life.

Preferred Qualifications

They value evidence of unusual technical range and persistence, but no single signal is required. Examples include medalist or finalist performance in ICPC, IOI, the Putnam, national mathematics or informatics olympiads, Codeforces, AtCoder, Topcoder, or similar competitions; exceptional open-source work; published systems research; or building a database, compiler, operating-system component, distributed system, or high-scale platform from scratch. If your strongest work does not fit a conventional resume, show it to us.

#Perks

• A competitive base salary. Expected U.S. range: $150,000-$220,000, calibrated for experience and location.
• Significant pre-seed founding equity/stock options so you share directly in the value of the infrastructure company you are helping create.
• Real architectural ownership over a technically ambitious system, with the mandate to make first-principles decisions and see them through to production.
• Comprehensive health, dental, and vision benefits.
• A small, high-agency team working on problems where better infrastructure can reshape robotics, emergency response, and urban operations.