Data Platform Engineer, Infrastructure

We need to output HTML fragment with sections: About the role? Actually the posting includes "About the Job" and "What You'll Get To Do", "What You Have", "The Extras That Set You Apart", "Field AI Onsite Work Philosophy", "Why Join Field AI?", "Be Part of the Next Robotics Revolution". Also location line at top: "Location: Irvine, CA". We need to not repeat job title as heading (the page already shows it). We need to use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). But we can use other headings if they match content? The instruction: "use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It suggests we should use those exact headings when appropriate. However we need to map content to these headings. The posting includes sections like About the Job (maybe "About the role"), What You'll Get To Do (Responsibilities), What You Have (Requirements/Qualifications/Skills), The Extras That Set You Apart (maybe Skills?), Field AI Onsite Work Philosophy (maybe Benefits? Actually it's about onsite work philosophy, could be part of Benefits or Schedule? Not exactly). Why Join Field AI? (maybe Benefits?). Be Part of the Next Robotics Revolution (maybe more about company). We need to include a section ONLY when posting has real, specific content for it. So we need to decide which sections to include. We must not include Pay or Schedule unless posting actually states them. There's no explicit pay or schedule info. There's mention of flexible hours to support work-life balance, but not a schedule. So we should not create Schedule section. Pay not mentioned. Benefits: there is mention of flexible hours, diverse workplace, etc. Could be considered Benefits. But we need to see if there is specific content about benefits: "Field AI Onsite Work Philosophy: Field AI believes in-person collaboration is essential... fully onsite roles based in our Irvine office, with flexible hours to support work-life balance." That's more about work arrangement, not benefits like health insurance. There's also "We are committed to fostering a diverse and inclusive workplace..." That's culture. Not explicit benefits like health, 401k. The instruction: "never create Pay/Schedule/Benefits sections unless the posting actually states them." So we should not create Benefits unless there is explicit benefits statement. There's no explicit benefits like health, retirement, etc. So we skip Benefits. We need to include About the role (maybe "About the Job") as

About the role

. Then Responsibilities (

Responsibilities

) for "What You'll Get To Do". Then Requirements/Qualifications/Skills: we have "What You Have" (education, experience). Also "The Extras That Set You Apart" could be additional qualifications/skills. Could combine into Requirements and Skills sections. But we need to avoid thin sections. Perhaps we make one

Requirements

covering education, experience, core skills, and another

Preferred Qualifications

for extras? But the instruction only lists certain headings; we can use others? It says "use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It implies we should use those headings when appropriate, but we could also use other headings if needed? Probably safer to stick to those headings. So we can have About the role, Responsibilities, Requirements, Qualifications, Skills. We need to map content. Let's extract: About the role: description of Field AI, Data Platform Team, About the Job paragraph. Could be a short prose. Responsibilities: bullet list from "What You'll Get To Do": design, build, operate cloud infrastructure; manage as code; provision and tune; own platform reliability; implement security; own cloud cost management; build observability stack; build internal tooling. Requirements: maybe education and years experience: Bachelor's or Master's degree in CS, Engineering, or related technical field; 3–5+ years experience in infrastructure, platform, DevOps, or SRE roles, ideally supporting data-intensive systems. Qualifications: maybe strong experience with major cloud (AWS or GCP), Kubernetes, IaC (Terraform); strong programming skills in Python, Go, etc.; experience operating production systems; working knowledge of data infrastructure components; experience with security fundamentals. Skills: maybe problem-solving, interdisciplinary teamwork. Extras: could be additional qualifications: experience supporting data or ML platforms; experience with high-volume telemetry/IoT/edge fleets; track record of significant cloud cost optimization; prior experience as early platform/infrastructure hire building from zero. We could put extras under Skills or Qualifications. But we need to avoid thin sections. Perhaps combine Qualifications and Skills into one section? But we need to follow instruction: use those headings when appropriate. Could have Requirements, Qualifications, Skills each with content. We also have location line: "Location: Irvine, CA". Should we include as a short

? The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So location is minor metadata; we can include a short

at top:

Location: Irvine, CA

. We must remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The posting includes a lot of EEO statement, AI tools note, etc. We need to strip those. Thus final HTML fragment: start with

Location: Irvine, CA

. Then

About the role

with prose summarizing Field AI and Data Platform Team and About the Job. Then

Responsibilities

with

• items. Then

  Requirements

  with
  • for degree and years experience. Then

    Qualifications

    with
    • for cloud, Kubernetes, IaC, programming, production systems, data infra, security. Then

      Skills

      with
      • for problem-solving, interdisciplinary teamwork, maybe extras? Could also include extras under Skills. We need to preserve ALL substantive information; do not invent or summarize away detail. So we must keep all details from the posting, but we can condense into bullet points but must not lose info. Let's list all substantive details: From About Field AI paragraph: "Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven(1) approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications." Also "About Field AI Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact. Learn more at https://fieldai.com." Also "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." Also "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." We need to preserve all that. Could be a few paragraphs. Responsibilities bullet list: each item from "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 Requirements bullet list: - 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 Qualifications bullet list: - 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 Extras (The Extras That Set You Apart) bullet list: - 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 We could place extras under Skills or Qualifications. But we have already used Skills for problem-solving etc. Could add extras under Skills as additional bullet points. But we need to avoid thin sections. Skills section currently would have problem-solving and ability to work in interdisciplinary teams plus the extras. That's enough. We must not include Pay, Schedule, Benefits. We also need to include location line as short

        . We must not include any boilerplate like EEO statements, AI tools note, etc. Now produce HTML fragment. Let's craft:

        Location: Irvine, CA

        About the role

        Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact. Learn more at https://fieldai.com.

        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