Software Engineer, Data Engineering (Robotics)

Location: Irvine, California, United States; on-site

Company

hirify.global builds risk-aware, reliable, field-ready embodied AI systems for real robots, sensors, and field deployments.

What you will do

• Design, build, and maintain production data pipelines for robot telemetry, logs, sensor data, and operational events.
• Develop ingestion, transformation, and orchestration workflows using Airflow or similar tools.
• Build backend services, APIs, and internal tools for engineering, machine learning, analytics, and operations teams.
• Work with AWS cloud infrastructure, including 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 while scaling systems for growing fleets and larger datasets.

Requirements

• 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 with Python.
• Experience building and operating production data pipelines, with familiarity with Airflow or comparable orchestration tools.
• Experience with AWS services such as S3, Lambda, ECS, EC2, RDS, Redshift, Glue, Athena, and SQS.
• Understanding of testing, monitoring, debugging, incident response, and cross-functional collaboration for production systems.

Nice to have

• Experience with AWS CDK, Terraform, CloudFormation, or other infrastructure-as-code tools.
• Production experience with Kubernetes, CI/CD, and modern DevOps practices.
• 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.

Culture & Benefits

• Work directly with real robots, sensors, and field deployments.
• Build systems that are tested on hardware and improved through real-world operations.
• Collaborate across robotics, autonomy, infrastructure, deployment, ML, analytics, and operations teams.