Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Data Platform Engineer, Infrastructure
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type Full time
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, build, and operate cloud compute, storage, and networking for the data platform
Manage infrastructure and data services as code with Terraform and CI/CD
Own platform reliability, on-call, incident response, and capacity planning
Implement security and governance, including IAM, secrets, encryption, and audit logging
Manage cloud costs across storage and compute
From the employer’s posting
Design, build, and operate the cloud infrastructure for the data platform
Manage everything as code: Terraform/IaC, GitOps workflows, and CI/CD for infrastructure and data services.
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.
Education & alternatives
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.
About Field-Ai
Every robot we deploy generates a continuous stream of telemetry, sensor logs, and operational data from environments around the world.
In the employer’s words · Read in context
Posting record
Report an errorOpen 4 monthsWe first saw this posting 123 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 11, 2026123 days ago
- Recorded sightings
- 100
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 123
Up longer than most. Similar jobs usually come down between day 6 and day 55.
Well past Field-Ai’s usual: its jobs come down by about day 27.
From 13,175 similar postings that came down, and 5 of Field-Ai’s. Coming down is not always a hire.
Field-Ai is hiring
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Databricks
- GCP
- Kubernetes
- Terraform
- Go
Where the posting names them
- 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.
- 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.
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.
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.
- 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.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Applying through Lever
- No account needed: one form, and Lever reads your resume into the profile recruiters search.
Already applied? Track this application
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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 like.
We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we 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.
Employment type
Full time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Irvine, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.