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F1 Engineer Jobs in Oregon (NOW HIRING)

Five9

OR

... recall, and F1-score thinking to prompt performance measurement. Proven ability to translate ... AI Prompt Engineering for Developers, Anthropic Prompt Engineering certification, OpenAI Prompt ...

All JobsF1 Engineer JobsF1 Engineer Jobs in Oregon

F1 Engineer information

See Oregon salary details

$32.8K

$101.3K

$134.8K

How much do f1 engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for f1 engineer in Oregon is $101,284.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,600.00 and $122,600.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in specialized fields such as aerospace, petroleum, or software engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often includes bonuses, stock options, or profit sharing, particularly in large corporations or high-demand industries.

What are F1 Engineers?

F1 Engineers are specialized professionals who design, develop, and optimize the performance of Formula 1 cars. They work in various roles such as race engineers, performance engineers, and design engineers, collaborating closely with drivers and technical teams. Their responsibilities include analyzing data, improving car setups, and ensuring compliance with regulations to achieve maximum speed and reliability on the track. F1 Engineers play a crucial role in a team's success during both races and development phases.

What engineers can work in F1?

F1 teams employ various engineers including mechanical, aerodynamics, electronics, software, and systems engineers. These professionals typically have backgrounds in engineering disciplines, strong technical skills, and experience with high-performance vehicles and data analysis tools. They work in a fast-paced environment focused on optimizing car performance and reliability.

What are the key skills and qualifications needed to thrive as a F1 Engineer, and why are they important?

To thrive as a F1 Engineer, you need a deep understanding of mechanical or automotive engineering, advanced problem-solving abilities, and typically a relevant engineering degree. Familiarity with CAD software, telemetry systems, and simulation tools, as well as experience with rapid prototyping and data analysis platforms, is crucial. Excellent teamwork, communication, and the ability to perform under pressure distinguish top candidates in this high-stakes environment. These skills and qualities are vital to ensuring innovation, precision, and seamless collaboration in the fast-paced world of Formula 1 racing.

How much do F1 engineers earn?

F1 engineers typically earn between $50,000 and $150,000 annually, depending on experience, team size, and location. Senior engineers or those working for top teams can earn higher salaries, often supplemented with bonuses and benefits. Entry-level positions may start lower but can increase with expertise and performance.

What is the difference between F1 Engineer vs Race Engineer?

AspectF1 EngineerRace Engineer
CredentialsEngineering degree, motorsport certificationsEngineering degree, motorsport certifications
Work EnvironmentF1 teams, race tracks, engineering labsF1 teams, race tracks, engineering labs
Industry UsageDesign, development, testing of F1 carsCommunication, strategy, car setup during races
Primary FocusTechnical development and analysisReal-time race strategy and driver communication

While both F1 Engineers and Race Engineers work within the motorsport industry, F1 Engineers focus on the technical development and testing of the car, whereas Race Engineers handle real-time race strategy and driver communication during events. Both roles require engineering expertise and are integral to a team's success in Formula 1 racing.

What are some common challenges F1 Engineers face when working with race teams during a season?

F1 Engineers often encounter the challenge of adapting quickly to changing race conditions and regulations, which requires constant problem-solving and innovative thinking. They work in high-pressure environments where split-second decisions can impact race outcomes, and collaboration with drivers, mechanics, and other engineers is crucial. Additionally, balancing the need for performance improvements with strict technical regulations and tight deadlines can be demanding. These challenges make the role dynamic and rewarding for those who thrive in fast-paced, team-oriented settings.

Is 20 too old to start F1?

F1 engineering is a highly competitive field that typically favors candidates with strong backgrounds in engineering, physics, or related disciplines, often gained through university degrees and relevant experience. While most F1 engineers start their careers in their early to mid-20s, starting at age 20 is not too late, especially if you have the necessary skills, certifications, and a strong understanding of automotive technology. Success depends on your qualifications, experience, and ability to work in a fast-paced environment, rather than age alone.
What are popular job titles related to F1 Engineer jobs in Oregon? For F1 Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching F1 Engineer jobs in Oregon look for? The top searched job categories for F1 Engineer jobs in Oregon are:
F1 Engineer jobs near you
Infographic showing various F1 Engineer job openings in Oregon as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $101,284 per year, or $48.7 per hour.

WEM AQM Prompt Engineer

Five9

OR

Other

Posted 12 days ago

Job description

Five9 is one of the world's leading cloud contact center platforms, and our AI-powered Automated Quality Management (AQM) product is transforming how enterprises evaluate and improve agent performance. To support the accelerating adoption of Five9 AQM across our customer base, the Specialized Services team is building a dedicated Prompt Engineering practice.


We are seeking three WEM AQM Prompt Engineers to join this new capability team. These roles sit at the intersection of contact center domain expertise and applied AI - designing, testing, and optimizing the LLM prompts that power Five9 AQM's automated evaluation criteria. If you have spent years building Speech Analytics categories in Verint, category sets in NICE, or Topics in Genesys, you already think and work the way this role requires.


Why Your Speech Analytics Experience Maps Directly to This Role

The Five9 AQM Prompt Engineering workflow follows the same disciplined, iterative process that experienced Speech Analytics analysts use every day:

Speech Analytics / Verint AQMFive9 AQM Prompt EngineeringDefine category intent & scope Define prompt intent & evaluation scopeSelect & tag representative call samples Select evaluation call samplesIteratively tune keyword / phrase sets Iteratively refine prompt wording & logicTest against live call traffic Test prompt outputs against real callsValidate recall & precision metrics Validate pass / fail accuracy metricsDocument & hand off to QA team Document prompts for QA workflow


Key Responsibilities
Design, author, and iteratively optimize LLM evaluation prompts within Five9 AQM, translating quality management frameworks into accurate, testable prompt logic.
Partner with customers and internal delivery consultants during AQM implementation engagements to define evaluation scope, intent, and pass/fail criteria.
Select and analyses representative call samples to validate prompt performance; apply precision and recall thinking to measure and improve prompt accuracy.
Maintain a structured prompt library - versioning prompts, documenting changes, and managing prompt lifecycle from initial design through to production handover.
Collaborate with QA and Implementation teams to integrate prompt outputs into broader QM workflow design, including scoring forms and reporting.
Identify prompt failure patterns and apply structured debugging techniques, including chain-of-thought adjustments, instruction clarity improvements, and few-shot example tuning.
Contribute to the development of Five9 AQM prompt engineering standards, best practice documentation, and reusable prompt templates.
Support pre-sales activities by demonstrating Five9 AQM prompt capabilities and articulating the value of AI-driven quality evaluation to prospective customers.
Stay current with LLM developments, prompt engineering research, and the evolving Five9 AQM product roadmap.


Ideal Candidate Profile
The strongest candidates will come from a Speech Analytics background with hands-on experience designing and optimizing categories, category sets, or topic models in platforms such as Verint, NICE CX one, or Genesys - and who are ready to apply that same analytical rigor to LLM prompt design.


Key Requirements
Minimum 3 years' hands-on experience as a Speech Analytics Analyst, QM Analyst, or WEM Application Consultant with deep involvement in category/topic design and optimization in Verint (Categories/CategorySets), NICE (Category Sets), Genesys (Topics), or equivalent platforms.
Demonstrable prompt engineering skills - either via formal qualification or a verifiable portfolio of prompt design work (production prompts, evaluation outputs, or documented iteration cycles).
Strong understanding of contact center Quality Management processes, evaluation frameworks, and scoring methodologies.
Experience selecting and analyzing call/interaction samples for model validation; comfortable applying precision, recall, and F1-score thinking to prompt performance measurement.
Proven ability to translate business and QM requirements into structured, testable evaluation logic.
Excellent written communication skills - prompt engineering is fundamentally a writing discipline.
Experience working in a customer-facing or professional services environment.
BA/BS or equivalent experience.


Preferred Qualifications
Formal prompt engineering certification or coursework (e.g., DeepLearning.AI Prompt Engineering for Developers, Anthropic Prompt Engineering certification, OpenAI Prompt Engineering course, or equivalent).
Hands-on experience with one or more major LLM platforms (OpenAI, Anthropic Claude, Google Gemini, or similar) including direct API or playground usage.
Prior exposure to Five9 AQM or equivalent AI-native QM solutions.
Experience with NICE Enlighten, Qualtrics, Medallia, or other AI-driven analytics platforms.
Familiarity with JSON, basic scripting, or no-code automation tools - useful for prompt testing workflows.
Experience developing training materials or internal knowledge base documentation.
Background in compliance-driven QM environments (financial services, healthcare, utilities).


Key Competencies
Analytical Rigor - applies structured, data-driven thinking to prompt design and performance measurement.
Linguistic Precision - writes clear, unambiguous instructions; understands how wording choices affect model behavior.
Iterative Mindset - comfortable with test-and-learn cycles; treats prompt refinement as an ongoing discipline, not a one-time task.
Domain Expertise - deep understanding of contact center operations, QM frameworks, and agent evaluation best practices.
Customer Orientation - able to translate client QM goals into technical prompt requirements and communicate findings clearly to non-technical stakeholders.
Intellectual Curiosity - keeps pace with the rapidly evolving LLM and generative AI landscape.


About Five9 WEM Specialized Services
The Specialized Services team within Five9 Professional Services delivers expert-led implementation, optimization, and advisory engagements across the Five9 WEM portfolio. Our AQM Prompt Engineering practice is a newly established center of excellence, designed to ensure that customers realize the full potential of Five9's AI-powered
quality management capabilities. These roles offer the opportunity to be founding members of a high-impact team at the leading edge of AI adoption in the contact center industry.

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