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Hardware Test & Reliability Engineer

Job in Mission, Johnson County, Kansas, 66201, USA
Listing for: Arable Labs, Inc.
Full Time position
Listed on 2026-02-16
Job specializations:
  • Engineering
    Systems Engineer, Electronics Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Overview

Arable is looking for a forward-thinking Hardware Test & Reliability Engineer to join our engineering team. In this role, you will act as the primary owner of product validation, ensuring that our hardware not only functions correctly on the bench but survives the rigors of the real world. This is an end-to-end role ideal for an engineer who enjoys the intersection of design verification, hands-on lab work, and data-driven analysis.

You will work side-by-side with design engineers to bring up new prototypes, build automated test fixtures, and rigorously stress-test our systems to uncover weak points before they reach our customers. We are looking for an "AI-native" thinker—someone who sees AI tools not just as a novelty, but as a core part of their engineering toolkit to accelerate coding, analysis, and problem-solving.

Responsibilities
  • Product Validation & NPI Support
  • Own the Master Test Plan for new hardware introductions. You will execute Design Verification Testing (DVT) to ensure new designs meet all electrical and functional specifications. This includes supporting board bring-up, validating power rails and communication buses, and collaborating with firmware teams to debug early prototypes.
  • Reliability & Environmental Qualification Oversight
  • Partner with our external manufacturing partners (ODMs) to manage comprehensive environmental qualification and ongoing reliability testing campaigns. Help define the test specifications (including HALT, thermal cycling, and Ingress Protection), negotiate test coverage and schedules, and scrutinize test data to ensure our hardware meets strict reliability standards.
  • Root Cause Analysis & Forensics
  • Lead the investigation of hardware failures from both the production line and the field. You will perform hands-on tear downs and forensic analysis to identify the root cause of failures—whether they are component defects, manufacturing issues, or design gaps—and drive corrective actions.
  • Test Automation & Fixture Development
  • Design and build electromechanical test fixtures to support lab validation and reliability testing. You will utilize Python to automate instrumentation (power supplies, data loggers) and streamline data collection, reducing the manual burden of repetitive testing.
  • Data-Driven Quality Improvement
  • Manage the closed-loop quality process (FRACAS). You will track failure trends, analyze fleet telemetry data to catch emerging issues, and present clear, data-backed recommendations to the engineering team to improve future designs.
Required Qualifications
  • Experience: 2–4 years of experience in hardware validation, test engineering, or reliability (projects involving embedded systems or outdoor electronics are a plus).
  • Lab

    Competency:

    Strong hands-on skills with standard lab equipment (oscilloscopes, DMMs, logic analyzers, soldering stations) and a comfort level with modifying hardware for test access.
  • Automation

    Skills:

    Proficiency in Python for test automation and data analysis. You should be comfortable writing scripts to interface with hardware or parse large datasets.
  • Engineering Fundamentals: A solid understanding of electronics (analog/digital) and mechanical basics, with the ability to read schematics and understand firmware logic.
  • Education: BS in Electrical Engineering, Mechatronics, or a related field.
  • Travel: Willingness to travel domestically (approx. 15-20%) to support field trials or environmental testing.
The AI-Augmented Advantage
  • Modern Workflow: We prioritize candidates who actively use AI/LLM tools to enhance their productivity. We are looking for engineers who use these tools to write test scripts faster, auto-summarize complex logs, or generate SQL queries for data mining.
  • Adaptive Thinking: Ability to use data and modern tools to quickly learn new technical domains—whether it’s understanding a new sensor protocol or troubleshooting a battery chemistry issue.
What Success Looks Like
  • 30 Days: You have mastered the lab environment, are independently running tests on current prototypes, and are using AI tools to streamline the weekly failure analysis reporting.
  • 90 Days: You have successfully executed the verification plan for the…
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