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Automated Reasoning Jobs in Utah (NOW HIRING)

Yantran LLC

Ai/ML Engineer -Agentic AI

Magna, UT

... automated production management services. By unifying classical ML with agentic AI, we deliver ... Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure ...

Danone

Maintenance Mechanic - Night Shift

West Jordan, UT

$23.25 - $30/hr

Troubleshooting equipment and parts failures using reasoning and analysis, and participating in ... Regularly climb ladders, stairs, steps, stools, and multiple levels of stairs inside our automated ...

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Automated Reasoning information

What are some common challenges faced by professionals working in Automated Reasoning roles?

Professionals in Automated Reasoning often encounter challenges such as handling highly complex logical problems, ensuring the scalability of reasoning algorithms, and integrating automated reasoning tools with existing systems. Collaborating with interdisciplinary teams—including software engineers, data scientists, and domain experts—can present communication hurdles, as explaining formal logic concepts to non-experts is sometimes necessary. Additionally, staying up-to-date with the latest research and advancements in theorem proving and formal verification is crucial for continued success in this rapidly evolving field.

What are the key skills and qualifications needed to thrive as an Automated Reasoning Engineer, and why are they important?

To thrive as an Automated Reasoning Engineer, you need a strong background in computer science, logic, and formal verification, often supported by an advanced degree in a related field. Familiarity with formal methods tools (such as SMT solvers, model checkers), programming languages like Python, C++, or OCaml, and experience with verification frameworks are typically important. Analytical thinking, problem-solving, and effective communication skills help engineers tackle complex proofs and collaborate with interdisciplinary teams. These skills are crucial for ensuring the reliability and correctness of software and hardware systems in safety-critical environments.

What is automated reasoning?

Automated reasoning is a field of computer science and mathematical logic dedicated to understanding how reasoning can be automated using computers. It involves developing algorithms and software that allow computers to prove theorems, verify software and hardware systems, and solve logical problems. Automated reasoning is used in areas such as formal verification, artificial intelligence, and knowledge representation, helping to ensure systems behave as intended and are free of certain types of errors.
What are popular job titles related to Automated Reasoning jobs in Utah? For Automated Reasoning jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Automated Reasoning jobs in Utah look for? The top searched job categories for Automated Reasoning jobs in Utah are:
What cities in Utah are hiring for Automated Reasoning jobs? Cities in Utah with the most Automated Reasoning job openings:
Automated Reasoning jobs near you
Infographic showing various Automated Reasoning job openings in Utah as of May 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.
Senior Software Engineer in Test (AI Agentic Systems)

Senior Software Engineer in Test (AI Agentic Systems)

Collective Health

Lehi, UT • Hybrid

$103K - $134K/yr

Other

Medical, Retirement, PTO

Posted 11 days ago

Job description

This is not a traditional QA role. You will be the quality owner for an LLM-based multi-agent pipeline that autonomously adjudicates health insurance claims for self-funded plan sponsors. You are building a Three-Tier Evaluation Framework to ensure our Gemini-powered agents reason correctly, call tools accurately, and produce DOL-ready outcomes.

You will work at the intersection of Vertex AI, healthcare compliance, and high-scale data engineering. Your work directly determines whether claims are paid correctly and whether the company can withstand a Department of Labor (DOL) or state DOI audit. The stakes are real, the domain is hard, and the problems are genuinely novel.

What you'll do:
  • Outcome Evaluation (The "What")
    • Golden Set Governance: Build and maintain a versioned library of "Grounding Data" results by working with senior claims examiners to define "Ground Truth."
    • Model-as-a-Judge Automation: Design automated "LLM-grading-LLM" workflows using custom rubrics to score factual grounding and policy compliance.
    • Semantic Assertion Framework: Develop testing libraries that move beyond string matching to validate semantic equivalence and numerical accuracy in agent outputs.
  • Trajectory Evaluation (The "How")
    • Function-Call Auditing: Use Vertex AI traces to programmatically verify that mandatory tools (via MCP) were invoked with correct arguments.
    • Orchestration Logic Validation: Assert that agents respect defined priorities across the four architectural layers: Data & Knowledge, Orchestration, Agentic Reasoning, and Tooling.
    • Reasoning Trace Auditing: Ensure every autonomous decision is traceable to a specific SOP sentence and a live API data point.
  • Continuous Automated Regression (The "Always")
    • CI/CD Integration: Every prompt or model update in Vertex AI Prompt Management must trigger an automated regression run.
    • Auto-SxS: Own the automated pairwise comparison process to detect logic drift between "New" and "Production" agent versions.
    • Mocking & Resilience: Build a Vertex AI/ADK mocking layer to simulate model responses, allowing for thousands of logic tests in seconds with zero API costs.
To be successful in this role, you'll need:
  • Required Skills (The Core Bar)
    • Python SDET Expertise: Expert in Python and pytest, specifically building custom mocking frameworks for external APIs (Vertex AI/ADK).
    • AI/LLM Observability: Hands-on experience with Vertex AI Experiments, Auto-SxS, and Cloud Logging for trace analysis.
    • Data Literacy: Expert-level SQL (BigQuery) and Pandas skills to "diff" massive datasets and identify adjudication discrepancies.
    • Prompt Engineering for QA: Ability to analyze "System Instructions" and refine prompts based on failed test cases to close logic gaps.
    • Architectural Testing: Experience testing multi-layer systems involving RAG (Vertex AI Search), state management (LangGraph), and function calling.
  • Preferred Skills (The "Nice-to-Haves")
    • Healthcare/Claims Domain: Familiarity with claims adjudication concepts (pend reason codes, COB, eligibility, stop-loss).
    • Compliance Knowledge: Understanding of HIPAA/PHI handling and writing test evidence for regulatory bodies (DOL/DOI).
    • Human-in-the-Loop Testing: Experience in "Shadow Mode" monitoring-comparing agent decisions against human expert (MCA) baselines.
Pay Transparency Statement 

This is a hybrid position based out of our Lehi office, with the expectation of being in office at least two weekdays per week. #LI-hybrid

The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for 115000 stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at https://jobs.collectivehealth.com/benefits/.

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