Data Platform Engineer, Infrastructure

FieldAI; Irvine (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

FieldAI’s Irvine team is building risk-aware, field-ready AI systems for robotics. As a Data Platform Engineer, you will own cloud infrastructure powering data, logs, and model training across a fleet of robots.

Collaborate with analytics, edge, and robotics teams to keep systems reliable, secure, and cost-efficient, with a focus on Kubernetes, IaC, and scalable data pipelines. You will contribute to security, governance, and observability while enabling engineers to ship features quickly.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 3–5+ years of experience in infrastructure, platform, DevOps, or SRE roles, ideally supporting data-intensive systems.
• Strong experience with a major cloud (AWS or GCP), Kubernetes, and infrastructure-as-code (Terraform or similar).
• Strong programming skills in Python, Go, or similar for automation and internal tooling.
• Experience operating production systems: monitoring, alerting, incident response, and capacity planning.
• Working knowledge of data infrastructure components (warehouses, object storage, streaming systems, orchestrators) and what they demand from underlying infrastructure.
• Experience with security fundamentals: IAM, network security, secrets management.
• Strong problem-solving skills and ability to work in interdisciplinary teams.

Responsibilities

• Design, build, and operate the cloud infrastructure for the data platform: compute, storage, and networking.
• Manage everything as code: Terraform/IaC, GitOps workflows, and CI/CD for infrastructure and data services.
• Provision and tune infrastructure for heavy workloads: large-scale sensor data processing and ML training jobs.
• Own platform reliability: SLAs/SLOs, on-call practices, incident response, and capacity planning.
• Implement security and governance: IAM, secrets management, encryption, audit logging, environment isolation.
• Own cloud cost management: monitoring, budgeting, optimization across storage and compute.
• Build observability stack (metrics, logging, tracing) for data platform services.
• Build internal tooling so pipeline and analytics engineers can ship without infra expertise.

Skills

Python

Go

Cloud platforms

Kubernetes

IaC (Terraform)

CI/CD

Monitoring/Observability

Security basics

Education

Bachelor's or Master's in CS/Engineering

Tools

Terraform

GitOps

Job description

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk‑aware, reliable, field‑ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data‑driven approaches or pure transformer‑only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.

About the Job

As a Data Platform Engineer, Infrastructure, you will build and operate the cloud foundation the entire data platform runs on — the systems every robot log, dashboard, and model‑training run depends on. You will collaborate with pipeline and analytics engineers, as well as edge and robotics teams, to keep the platform reliable, secure, and cost‑efficient as our fleet grows.

About the Data Platform Team

Every robot we deploy generates a continuous stream of telemetry, sensor logs, and operational data from environments around the world. The Data Platform team builds the systems that capture every autonomy intervention, anomaly, and operational signal from globally deployed robots, classify them, and turn them into the ranked problem list that drives our engineering roadmap.

What You’ll Get To Do

• Design, build, and operate the cloud infrastructure for the data platform: compute (Kubernetes, serverless, batch clusters), storage (object stores, warehouse/lakehouse), and networking.
• Manage everything as code: Terraform/IaC, GitOps workflows, and CI/CD for infrastructure and data services.
• Provision and tune infrastructure for heavy workloads: large‑scale sensor data processing, distributed pipeline execution, and ML training and evaluation jobs.
• Own platform reliability: SLAs/SLOs, on‑call practices, incident response, and capacity planning as fleet data volume grows.
• Implement security and governance: IAM and access controls, secrets management, encryption, audit logging, and environment isolation.
• Own cloud cost management: monitoring, budgeting, and optimization across storage and compute.
• Build the observability stack (metrics, logging, tracing) for all data platform services.
• Build internal tooling and paved paths so pipeline and analytics engineers can ship without becoming infrastructure experts.

What You Have

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 3–5+ years of experience in infrastructure, platform, DevOps, or SRE roles, ideally supporting data‑intensive systems.
• Strong experience with a major cloud (AWS or GCP), Kubernetes, and infrastructure‑as‑code (Terraform or similar).
• Strong programming skills in Python, Go, or similar for automation and internal tooling.
• Experience operating production systems: monitoring, alerting, incident response, and capacity planning.
• Working knowledge of data infrastructure components (warehouses, object storage, streaming systems, orchestrators) and what they demand from underlying infrastructure.
• Experience with security fundamentals: IAM, network security, secrets management.
• Strong problem‑solving skills and ability to work in interdisciplinary teams.

The Extras That Set You Apart

• Experience supporting data or ML platforms specifically (Spark/Databricks clusters, GPU scheduling, feature stores).
• Experience with high‑volume telemetry or IoT/edge fleets.
• Track record of significant cloud cost optimization.
• Prior experience as an early platform/infrastructure hire, building from zero.

Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job‑related knowledge, skills, experience, and the Irvine, California market.

Why Join FieldAI in Irvine?

In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real‑world use.

You will collaborate with a world‑class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.

Be Part of the Next Robotics Revolution

We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.

Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field‑ready autonomy looks to be .

We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.