{"id":624230,"url":"https://alion.io/job/fieldai-software-engineer-data-engineering","title":"Software Engineer, Data Engineering","company":{"id":672883,"name":"FieldAI","domain":"fieldai.com","url":"https://alion.io/company/fieldai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":88,"open_postings":91,"ghost_share":0,"stale_share":0.264,"repost_share":0,"time_to_fill_p50_days":61,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Irvine, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":115000,"max":170000,"currency":"USD","period":"year","gross":null,"usd_annual":170000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS CDK","optional":false},{"name":"AWS Lambda","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Databricks","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Kubernetes","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Terraform","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-08-01T01:03:02Z","employer_posted_date":"2026-08-01","last_verified_at":"2026-10-18T12:51:37Z","board_verified":true,"closed_at":null,"days_open":78,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":78},"description":"About the Job\nField 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.\nWhat You Will Get To Do\nDesign, build, and maintain production data pipelines for robot telemetry, logs, sensor data, and operational events.\n\nBuild reliable ingestion, transformation, and orchestration workflows using tools such as Airflow.\n\nDevelop backend services, APIs, and internal tools that make data accessible to engineering, ML, analytics, and operations teams.\n\nWork with cloud infrastructure on AWS, including object storage, compute, databases, queues, and data processing services.\n\nImprove pipeline reliability through monitoring, retries, backfills, schema validation, and data quality checks.\n\nCollaborate with robotics, autonomy, infrastructure, and deployment teams to support real-world robot operations.\n\nHelp scale data systems for growing fleets and increasingly large datasets.\n\nWhat You Have\nBachelor's or Master's degree in Computer Science, Engineering, or a related technical field.\n\n3+ years of experience in data engineering, backend engineering, infrastructure, or platform engineering.\n\nStrong software engineering skills, preferably in Python.\n\nExperience building and operating data pipelines in production.\n\nFamiliarity with Airflow or similar workflow orchestration tools.\n\nExperience with AWS services such as S3, Lambda, ECS, EC2, RDS, Redshift, Glue, Athena, SQS, or related systems.\n\nGood understanding of testing, monitoring, debugging, and incident response for production systems.\n\nAbility to work across teams and translate messy real-world data problems into reliable systems.\n\nWhat Will Set You Apart\nExperience with AWS CDK, Terraform, CloudFormation, or other infrastructure-as-code tools.\n\nExperience with Kubernetes, including deploying, operating, or debugging workloads in production clusters.\n\nExperience with robotics, autonomy, IoT, fleet telemetry, time-series data, or sensor-heavy systems.\n\nExperience with data lake or warehouse systems such as Redshift, Snowflake, BigQuery, Databricks, or Athena.\n\nFamiliarity with CI/CD and modern DevOps practices.","description_format":"text","description_chars":2519,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotics AI","Industrial AI"],"lifecycle":[{"event":"open","at":"2026-09-10T18:57:39Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 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