Senior AI Engineer

Procore

Austin, TXJob$141–194K/yrPosted 1w agoStill listed 6 days ago

Most applications go out cold — see where you stand first. No sign-up to start.

You apply on the employer's site, with no Olive account needed.

Watch jobs like this.

Don't just apply. Show up ready.

Olive works from this exact posting.

At a glance

Compensation
$141–194K/yr
Location
Austin, TX
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Procore is hiring a Senior AI Engineer for its Evals & Goldsets team, which measures and improves AI agents serving the construction industry. The engineer will build evaluation systems, production tracing, and goldsets and benchmarks, partnering with data and ML engineers to improve evaluation speed, cost, trustworthiness, and agent behavior. The hybrid role is based in Austin and combines hands-on engineering with architecture, design review, and mentoring.

Skills & qualifications

RequiredNice to have

Skills

Python (Programming Language)Machine LearningData PipelineExtract Transform Load (ETL)DatabricksTypeScriptLLM EvaluationLLM-as-JudgeRubric DesignGoldset CurationJudge Agreement MeasurementLLM ObservabilityLangfuseBraintrustData PipelinesETLStreaming Data SystemsSnowflakeCommunicationInfluencing Teams

Qualifications

5+ Years Engineering ExperienceComputer Science or Related Technical Degree or Equivalent Experience

Full job description

We're looking for a Senior AI Engineer to join Procore's Evals & Goldsets team, which measures and improves the quality of the AI agents we ship to the construction industry. You'll build and run the systems that tell our AI teams how well their agents are doing: production tracing in Langfuse and Databricks, our online LLM judge, and the goldsets and benchmarks behind our offline evals.

As a Senior AI Engineer, you will partner with data and ML engineers to make our evals faster, cheaper, more trustworthy, and harder to saturate, and you'll turn production traces into feedback loops that improve agent behavior. We're a small, fast-moving team that pairs hands-on building with architecture and review, and we value engineers who are rigorous about measurement and comfortable with ambiguity. If you want to shape how AI in construction gets tested and improved, come join us.

This hybrid position reports to the Engineering Manager for Evals & Goldsets and will be based in our Austin, TX office.

What you’ll do:

  • Improve our online evals: LLM judge accuracy, calibration, and the infrastructure that runs it in production.
  • Build and maintain production trace infrastructure with Langfuse and Databricks.
  • Build and maintain data pipelines for the goldsets behind our evals, including annotation and quality checks.
  • Build agentic loops that mine production traces for failures and turn them into new eval cases and agent improvements.
  • Improve the runtime, cost, and reliability of our online and offline eval pipelines.
  • Contribute code and architecture, review designs, and mentor other engineers on the team.

What we’re looking for:

  • 5+ years of experience in software, AI, or ML engineering.
  • Strong proficiency in Python; experience with TypeScript is a plus.
  • Experience evaluating LLM systems, such as LLM-as-judge, rubric design, goldset curation, or measuring judge agreement.
  • Experience with LLM observability or evaluation tools such as Langfuse, Braintrust, or similar.
  • Experience building data pipelines, ETL processes, or streaming data systems.
  • Experience with analytics platforms and data warehouses such as Databricks or Snowflake.
  • Ability to communicate eval results clearly and influence the teams that build on them.
  • Degree in computer science or a related technical field, or equivalent practical experience.

Additional Information

Base Pay Range: 140,960.00 - 193,820.00 USD Annual This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate’s job-related skills, experience, education or training, and location.

For Los Angeles County (unincorporated) Candidates: Procore will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable federal, state, and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

A criminal history may have a direct, adverse, and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. appropriately managing, accessing, and handling confidential information including proprietary and trade secret information, as well as accessing Procore's information technology systems and platforms; 2. interacting with and occasionally having unsupervised contact with internal/external customers, stakeholders, and/or colleagues; and 3. exercising sound judgment.

How this job compares

Set against the 6,998 open AI Engineer jobs on Olive Jobs, counted November 3, 2026.

Pay
  • This posting$141–194K/yr
  • Texas median$122–235K/yr333 salary ranges
  • US median$131–236K/yr5,785 salary ranges

This range's midpoint, $167K, is 8% below the Texas median midpoint ($181K) — in the middle half of AI Engineer salary ranges in Texas.

Openings
Olive Jobs lists 436 open AI Engineer jobs in Texas and 6,998 across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most in Texas
Experience
This posting asks for at least 5 years of experience; AI Engineer postings that state a minimum ask for 5 years at the median (5,939 postings).
Education
2,904 of the 6,998 open AI Engineer jobs (41%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

Prepare for this role

You've read the whole posting — now see how you match it.