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Principal Performance Architect Jobs in Oregon (NOW HIRING)

OR · On-site

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... Create and execute operational testing strategies, including QA validation, performance testing ...

OR · On-site

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... performance expectations. * Contribute to and leverage reusable assets such as reference ...

OR · On-site

Role Overview We are looking for a Principal Solution Architect to join our Managed Services team ... performance goals. * Serve as a trusted advisor and senior technical leader across client ...

Architect across the stack: Design end-to-end solutions - from data model to API to UI - that are ... Conduct rigorous testing to guarantee performance, scalability, and reliability of updated or newly ...

... high-performance computing (HPC), cloud service providers (CSP), gaming, virtual reality, and ... Come join the CPU architecture team and help us the boundaries for all our CPU products! What you ...

OR · On-site

... platform architecture decisions: app structure, state management, offline handling, performance ... or principal IC level. Education Requirements: Bachelor's Degree in Computer Science or related ...

OR · Hybrid

Job Title: Principal Cloud Network Engineer Reports to: Sr. Director, Cloud and Engineering ... performance, DNS, and hybrid integration issues. * Demonstrated authority leading architecture ...

Our work includes enterprise architectural assessments, systems engineering and integration, test ... Optimize platform performance, scalability, networking, storage, resource utilization, and overall ...

... principal technical authority across all project teams. * This individual will establish and ... performance, scalability, and cost-effectiveness. Required Experience/Qualifications * Bachelor ...

The Principal Systems Engineer will define system-level requirements, ensure cross-functional ... performance, reliability, and scalability. Key Responsibilities System Architecture & Technical ...

As a Principal Logic Design Engineer , you will play a pivotal role in the micro-architecture and design of our next- generation high performance and cutting-edge memory controllers for data centers ...

Architecture, Systems Design - Help design and evolve SMC as an online school OS, balancing product ... and performance work. - Model good practices in testing, observability, secure coding, and ...

As a Principal Logic Design Engineer , you will play a pivotal role in the micro-architecture and design of our next- generation high performance and cutting-edge memory controllers for data centers ...

Summary Flexential is hiring a Principal Platform Engineer in the IT organization to plan roadmaps ... architecture. * Engineering Management - 4+ years, Hiring, team building, performance management ...

Showing results 21-40

Principal Performance Architect information

See Oregon salary details

$85.1K

$181.2K

$244.2K

How much do principal performance architect jobs pay per year?

As of Aug 12, 2026, the average yearly pay for principal performance architect in Oregon is $181,200.00, according to ZipRecruiter salary data. Most workers in this role earn between $153,300.00 and $205,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a principal performance architect, and why are they important?

To thrive as a Principal Performance Architect, you need deep expertise in systems architecture, performance engineering, and scalability, often backed by a degree in computer science or related fields. Familiarity with performance analysis tools (e.g., JMeter, Dynatrace), cloud platforms, and scripting languages, along with relevant certifications, is typically expected. Exceptional problem-solving, communication, and leadership skills help you collaborate with cross-functional teams and drive best practices. These skills ensure that large-scale systems operate efficiently, meet business requirements, and deliver optimal user experiences.

What are the typical challenges a principal performance architect faces when optimizing large-scale enterprise systems?

Principal Performance Architects often encounter challenges such as balancing system scalability with cost efficiency, identifying performance bottlenecks in complex architectures, and aligning optimization strategies with evolving business goals. They must work closely with cross-functional teams—including developers, infrastructure engineers, and product managers—to ensure that solutions are both technically robust and aligned with user needs. Navigating legacy systems and integrating new technologies can also present unique hurdles, requiring strong analytical skills and deep experience with performance testing tools.

What is a principal performance architect?

Principal Performance Architects are senior-level professionals responsible for designing, analyzing, and optimizing the performance of software systems or IT infrastructure. They work to ensure that applications and services run efficiently, reliably, and can scale effectively with increased usage. Their role often involves identifying bottlenecks, recommending improvements, and establishing best practices for performance across development teams. With extensive experience, they also mentor other engineers and collaborate with stakeholders to meet organizational performance goals.

What is the difference between Principal Performance Architect vs Performance Engineer?

AspectPrincipal Performance ArchitectPerformance Engineer
CredentialsTypically requires advanced degrees and extensive experience in performance architectureUsually requires a bachelor's or master's in computer science or related field, with relevant performance testing certifications
Work EnvironmentFocuses on designing and overseeing performance strategies across large systems and enterprise environmentsConducts performance testing, analysis, and tuning on specific applications or components
Employer & Industry UsageCommon in large tech firms, financial institutions, and enterprise software companiesUsed across various industries including IT, software development, and consulting firms

The Principal Performance Architect typically leads performance strategy and architecture at an enterprise level, requiring more experience and strategic oversight. Performance Engineers focus on testing and optimizing specific applications or systems. Both roles are essential but differ mainly in scope and seniority.

What are popular job titles related to Principal Performance Architect jobs in Oregon? For Principal Performance Architect jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Principal Performance Architect jobs in Oregon look for? The top searched job categories for Principal Performance Architect jobs in Oregon are:
What cities in Oregon are hiring for Principal Performance Architect jobs? Cities in Oregon with the most Principal Performance Architect job openings:
Infographic showing various Principal Performance Architect job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $181,200 per year, or $87.1 per hour.

Machine Learning Principal Solutions Architect

phData

OR • On-site

Full-time

Dental, Vision, Retirement, PTO

Re-posted 6 days ago


Job description

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that deliver measurable business value for our clients. You will take full ownership of strategic AI/ML projects from vision and solution design through deployment and ongoing optimization while ensuring that models can be trained, tuned, and operated reliably using client data. You will collaborate closely with clients, Sales, data scientists, ML engineers, and platform teams to deliver high-quality solutions and advance phData's delivery excellence.

Key ResponsibilitiesClient Delivery
  • Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, from model inference, retraining, and monitoring through to production operations.
  • Translate business and data science requirements into scalable, secure, and resilient architectures that align with phData methodologies, standards, and best practices.
  • Design and create environments for data scientists to build, train, test, and tune AI/ML models and applications using relevant client data.
  • Work within customer systems to extract data from a variety of sources and place it within analytical environments to support model development, training, and tuning.
  • Define deployment approaches and production infrastructure for AI/ML models and applications, ensuring that businesses can reliably consume and maintain the solutions we deliver.
  • Demonstrate the business value of data by partnering with data scientists to manipulate and transform data into actionable insights and deployable machine learning models.
  • Create and execute operational testing strategies, including QA validation, performance testing, and implementation plans to support testing and deployment of AI/ML solutions.
  • Ensure the quality, reliability, and observability of delivered solutions through rigorous testing, documentation, and monitoring.
Collaboration & Leadership
  • Collaborate with cross-functional partners including data scientists, ML engineers, data engineers, platform/DevOps, and business stakeholders to deliver successful client engagements.
  • Provide technical and strategic leadership during workshops, discovery sessions, architecture and design reviews, and project delivery.
  • Partner closely with Sales and account leadership to drive account expansion, identify new opportunities, and ensure long-term client value on strategic accounts.
  • Take full ownership of client success within AI/ML projects, including planning and vision-crafting, managing client expectations, and handling escalations in a proactive and outcome-oriented manner.
  • Ensure high quality in deliverables through code reviews, documentation, testing, governance, and adherence to security and compliance standards.
  • Serve as a visible technical leader and point of escalation for complex AI/ML challenges within key customer engagements.
Practice & Firm Contribution
  • Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, and playbooks focused on AI/ML and MLOps.
  • Mentor and guide ML engineers, data scientists, and other team members to elevate the overall technical and consulting capabilities of the practice.
  • Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders.
Additional Responsibilities
  • Act as a trusted advisor to senior and executive client stakeholders, shaping AI/ML roadmaps, influencing strategic decisions, and guiding long-term initiatives.
  • Lead multiple work streams concurrently, ensuring alignment across technical teams, business stakeholders, and account leadership.
  • Help define and refine practice standards, reusable assets, and delivery frameworks that improve consistency, quality, and scalability of AI/ML engagements.
  • Champion a culture of customer obsession, continually seeking ways to increase client impact and satisfaction.
About You

You are a customer-obsessed technical leader and consultant who enjoys solving complex data and AI/ML challenges while building trusted relationships with clients. You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams. You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a blend of strong engineering skills, strategic thinking, and excellent communication to every engagement.

Required QualificationsExperience
  • 10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.

Technical / Functional Skills

  • Expertise in modern programming languages such as Python, Scala, Java, or similar, including experience developing APIs and web server applications using frameworks such as Flask, Django, or Spring.
  • Ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets, with strong working knowledge of SQL and the ability to write, debug, and optimize complex and distributed queries.
  • Hands-on experience with big data and analytics ecosystem technologies such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar platforms.
  • Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP.
  • Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera).
  • Proven experience deploying machine learning models into production environments and ensuring their performance, security, scalability, and reliability.
  • Complete software development lifecycle experience, including design, documentation, implementation, testing, deployment, and ongoing operations.
  • Excellent communication and presentation skills, with prior experience working directly with internal or external customers.
Consulting / Delivery Skills
  • Owning pre-sales and project scoping responsibilities
  • Proven Account Growth / Revenue Generation experience for external clients
  • Experience delivering projects for external or internal clients in a professional services, product, or consulting environment.
  • Ability to break down complex, ambiguous problems into structured, actionable steps and drive them through to completion.
  • Strong written and verbal communication skills in English, with the ability to present technical concepts to both technical and non-technical audiences.
  • Demonstrated customer obsession and a strong desire to make clients successful.
Collaboration & Ownership
  • Demonstrated ability to work effectively with distributed and cross-functional teams, including Sales, data scientists, ML engineers, data engineers, and business stakeholders.
  • Proven track record of taking ownership of client outcomes, managing multiple priorities and work streams, and delivering high-quality work with minimal supervision.
  • Comfort operating in client environments, quickly learning new systems and tools, and adapting solutions to fit existing architectures and processes.
Education
  • Bachelor's level degree in Computer Science or a related technical field, or equivalent practical experience preferred.
Preferred Qualifications

Preferred qualifications help candidates stand out but are not required for success in this role.

  • A Master's or other advanced degree in data science, computer science, or a related field.
  • Hands-on experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP.
  • Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Experience with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow, and with building enterprise-scale ML models.
  • Prior experience in a consulting role or working closely with clients on strategic data and AI/ML initiatives.
  • Relevant side projects such as contributions to open source technology stacks, technical communities, speaking, or writing.
Location & Time Zone Expectations

This role is based in the United States and operates primarily in the Central Time Zone.

  • We are a remote-first company, and you should be comfortable working with a distributed global team.
  • Some flexibility may be required to collaborate across time zones with colleagues and clients.
  • Client needs may occasionally require flexibility in working hours to support key milestones or workshops.
Why phData?
  • Impactful Work: Partner with leading organizations on meaningful data & AI initiatives.
  • Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
  • Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.

Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.

Benefits at phData

US:

  • Remote-First Work Environment
  • 401k plan with company match
  • Dental and Vision insurance
  • Home Office Equipment Stipend
  • Annual stipend for Learning and Development
  • Competitive comp, excellent benefits, 4 weeks PTO plan plus 10 Holidays (and other cool perks)