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Data Engineer (SE / Senior SE)

Santa Clara, CA

Pay
USD 130,000–200,000/year — pay source
Salary 130,000 – 200,000 USD per year Your opportunities joining PlusAI
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Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
Apply at Plus-2

What you’ll work on

Full posting
  • Define and compute driving performance metrics and the pipelines that evaluate them at fleet scale

  • Analyze road-test and simulation data to find regressions and anomalies in autonomy behavior

  • Build geospatial analytics showing where the virtual driver performs well and where it struggles

  • Build data foundations and tooling for release comparisons and gating decisions

  • Build AI agentic workflows that cluster, triage, and propose fixes for detected issues

From the employer’s posting
Define and compute driving performance metrics — covering safety, comfort, progress, interventions, and compliance — and build the scalable pipelines that evaluate them consistently across fleet and simulation data
Analyze road-test and simulation data in depth to identify trends, regressions, and anomalies in autonomy behavior
Build geospatial analytics over fleet driving data
Build the data foundations and tooling for release management, including release-over-release comparisons, readiness and gating criteria, and traceable evidence supporting release decisions
Build AI agentic workflows that triage detected issues at scale — clustering and deduplicating failures, attributing root cause, routing to the right owners, and proposing fixes with supporting evidence for engineering review

What you’ll bring

All qualifications

Core experience

  • Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks
  • Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis
  • Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation
  • Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders

Preferred experience

  • Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows
  • Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns
  • Experience with geospatial data and tooling, such as GIS formats, map matching, spatial indexing and joins, PostGIS, GeoPandas, or map-based visualization libraries
  • Experience with release engineering, quality gating, or automated regression detection
Qualification wording
Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks
Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis
Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation
Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders
Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows
Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns
Experience with geospatial data and tooling, such as GIS formats, map matching, spatial indexing and joins, PostGIS, GeoPandas, or map-based visualization libraries
Experience with release engineering, quality gating, or automated regression detection
Education & alternatives
Required Skills: - BS, MS, or PhD in Computer Science, engineering, or a related technical field, or equivalent practical experience - Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks

Tools in this posting

  • Python
  • Spark
  • Airflow
Source — Tool mentions in context
PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams. Knowing how well our virtual driver drives — and why it fell short — is what lets us ship with confidence. In this role, you will own that loop end to end: the metrics that quantify driving performance, the pipelines that compute them at fleet scale, the analysis that turns them into judgments about autonomy behavior — including where on the map that behavior changes — the data and tooling that gate software releases, and the agentic workflows that take a detected issue from triage to a proposed fix. You will work primarily in Python across large-scale data processing, geospatial analytics, evaluation frameworks, and LLM-powered automation. We welcome engineers from data engineering, analytics, geospatial, evaluation, or robotics backgrounds; prior autonomous-vehicle experience is helpful but not required. We are open to candidates at either the Engineer or Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.
- BS, MS, or PhD in Computer Science, engineering, or a related technical field, or equivalent practical experience - Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks - Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis
Preferred Skills: - Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows - Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns

Posting record

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Live
First seen by us
Aug 13, 2026 · 79 days ago
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38
Last seen by us
Oct 31, 2026
Employer says posted
Aug 10, 2026

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Job description

View original posting ↗

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

Knowing how well our virtual driver drives — and why it fell short — is what lets us ship with confidence. In this role, you will own that loop end to end: the metrics that quantify driving performance, the pipelines that compute them at fleet scale, the analysis that turns them into judgments about autonomy behavior — including where on the map that behavior changes — the data and tooling that gate software releases, and the agentic workflows that take a detected issue from triage to a proposed fix. You will work primarily in Python across large-scale data processing, geospatial analytics, evaluation frameworks, and LLM-powered automation. We welcome engineers from data engineering, analytics, geospatial, evaluation, or robotics backgrounds; prior autonomous-vehicle experience is helpful but not required.

We are open to candidates at either the Engineer or Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.

Responsibilities:

  • Define and compute driving performance metrics — covering safety, comfort, progress, interventions, and compliance — and build the scalable pipelines that evaluate them consistently across fleet and simulation data

  • Analyze road-test and simulation data in depth to identify trends, regressions, and anomalies in autonomy behavior, and turn them into clear findings that engineering teams act on

  • Build geospatial analytics over fleet driving data: map-matched metrics, route and corridor performance, location-based clustering of events and issues, and geographic coverage analysis that shows where the virtual driver performs well and where it struggles

  • Build the data foundations and tooling for release management, including release-over-release comparisons, readiness and gating criteria, and traceable evidence supporting release decisions

  • Build AI agentic workflows that triage detected issues at scale — clustering and deduplicating failures, attributing root cause, routing to the right owners, and proposing fixes with supporting evidence for engineering review

  • Ensure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts

Required Skills:

  • BS, MS, or PhD in Computer Science, engineering, or a related technical field, or equivalent practical experience

  • Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks

  • Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis

  • Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation

  • Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders

  • Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Preferred Skills:

  • Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows

  • Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns

  • Experience with geospatial data and tooling, such as GIS formats, map matching, spatial indexing and joins, PostGIS, GeoPandas, or map-based visualization libraries

  • Experience with release engineering, quality gating, or automated regression detection

  • Experience with autonomous vehicles, robotics, or other safety-critical systems

  • Experience building dashboards or analytics interfaces that expose metrics to users

Salary

130,000 – 200,000 USD per year

Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.

Employment type

Full-time

Source details

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Pay
Salary 130,000 – 200,000 USD per year Your opportunities joining PlusAI
Location & working pattern

Santa Clara, CA

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