Software Engineer, Data Engineering

Field Ai
Irvine, CA
On-siteCareer-pivot friendly

Who this role is best for

Strong fit for mid-level software engineers who build and operate data pipelines in robotics and AI domains, with a preference for hands-on, production-focused work in Southern California.

Best fit for

  • Mid-level engineers with production data pipeline experience and cloud infrastructure expertise
    — “3+ years of experience in data engineering, backend engineering, infrastructure, or platform engineering.”
  • Candidates who enjoy translating real-world data challenges into scalable systems
    — “Ability to work across teams and translate messy real-world data problems into reliable systems.”
  • Individuals with a background in robotics, IoT, or sensor-heavy data systems
    — “Experience with robotics, autonomy, IoT, fleet telemetry, time-series data, or sensor-heavy systems.”

Things to consider

  • Role requires working with real-world hardware and sensor data, not just simulation or theoretical models
    — “we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics”
  • Geographic preference for in-person presence in Irvine, CA, given the location emphasis
    — “Our headquarters is in Irvine, and we partner closely with teams there”

How to stand out

  • Emphasize end-to-end pipeline ownership and experience with Airflow or similar tools
    — “Build reliable ingestion, transformation, and orchestration workflows using tools such as Airflow.”
  • Highlight cloud infrastructure experience with AWS services like S3, Lambda, and Redshift
    — “Experience with AWS services such as S3, Lambda, ECS, EC2, RDS, Redshift, Glue, Athena, SQS, or related systems.”
  • Demonstrate familiarity with data quality checks and monitoring for production systems
    — “Improve pipeline reliability through monitoring, retries, backfills, schema validation, and data quality checks.”
  • Showcase skills in infrastructure-as-code with AWS CDK or Terraform if available
    — “Experience with AWS CDK, Terraform, CloudFormation, or other infrastructure-as-code tools.”
  • Mention any experience with Kubernetes or DevOps practices for added differentiation
    — “Familiarity with CI/CD and modern DevOps practices.”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Mid

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • reliable data pipelines
  • scalable data systems
  • accurate data ingestion
Typical background
data engineeringbackend engineeringinfrastructure

Skills & requirements

Required

Data PipelinesCloud InfrastructureAWS ServicesData Quality ChecksProduction Systems

Preferred

KubernetesData LakeCI/CDDevOps

Stack & domain

PythonAirflowAWSData EngineeringCloud Infrastructure

About the role

Original posting from Field Ai via Lever

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:

Field AI is looking for a Data Engineer to build reliable data pipelines and infrastructure for robotics data at scale. You will work on systems that move telemetry, logs, sensor data, and operational signals from deployed robots into the platforms used by autonomy, analytics, ML, and deployment teams. This role is ideal for someone with a strong software engineering background who enjoys building production systems, working with cloud infrastructure, and owning data pipelines end to end.

What You Will Get To Do:

-

Design, build, and maintain production data pipelines for robot telemetry, logs, sensor data, and operational events.

-

Build reliable ingestion, transformation, and orchestration workflows using tools such as Airflow.

-

Develop backend services, APIs, and internal tools that make data accessible to engineering, ML, analytics, and operations teams.

-

Work with cloud infrastructure on AWS, including object storage, compute, databases, queues, and data processing services.

-

Improve pipeline reliability through monitoring, retries, backfills, schema validation, and data quality checks.

-

Collaborate with robotics, autonomy, infrastructure, and deployment teams to support real-world robot operations.

-

Help scale data systems for growing fleets and increasingly large datasets.

What You Have:

-

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

-

3+ years of experience in data engineering, backend engineering, infrastructure, or platform engineering.

-

Strong software engineering skills, preferably in Python.

-

Experience building and operating data pipelines in production.

-

Familiarity with Airflow or similar workflow orchestration tools.

-

Experience with AWS services such as S3, Lambda, ECS, EC2, RDS, Redshift, Glue, Athena, SQS, or related systems.

-

Good understanding of testing, monitoring, debugging, and incident response for production systems.

-

Ability to work across teams and translate messy real-world data problems into reliable systems.

What Will Set You Apart:

-

Experience with AWS CDK, Terraform, CloudFormation, or other infrastructure-as-code tools.

-

Experience with Kubernetes, including deploying, operating, or debugging workloads in production clusters.

-

Experience with robotics, autonomy, IoT, fleet telemetry, time-series data, or sensor-heavy systems.

-

Experience with data lake or warehouse systems such as Redshift, Snowflake, BigQuery, Databricks, or Athena.

-

Familiarity with CI/CD and modern DevOps practices.

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 statu

Source: Field Ai careers (Lever)

Similar roles