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Principal Performance Architect Jobs in Michigan

Stellantis

Principal AI Engineer

Auburn Hills, MI · On-site

Architect and implement end-to-end LLM systems , including: * Prompt pipelines * Agent-based ... Experience designing systems that balance performance, scalability, cost, and accuracy . * Ability ...

Dematic

Software Principal Engineer

Grand Rapids, MI · On-site

$129K - $174K/yr

Job Summary : Dematic Corp. is seeking a Software Principal Engineer to join their Lifecycle ... database architecture and development, including schema design, performance optimization, and ...

Genesys

Architect and lead the development of agentic AI systems that automate and augment finance ... This role might also be eligible for a commission or performance-based bonus opportunities. $193 ...

Stellantis

Principal AI Engineer

Auburn Hills, MI

Architect and implement end‑to‑end LLM systems , including: * Prompt pipelines * Agent‑based ... Experience designing systems that balance performance, scalability, cost, and accuracy . * Ability ...

New

Socket.dev

MI · On-site

$140 - $210/hr

This role owns the design architecture, analytical approach, materials selection, manufacturing ... Partner with customers on requirements definition, performance trade studies, design reviews, and ...

New

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All JobsPrincipal Performance Architect JobsPrincipal Performance Architect Jobs in Michigan

Principal Performance Architect information

See Michigan salary details

$70.2K

$149.4K

$201.3K

How much do principal performance architect jobs pay per year?

As of Aug 10, 2026, the average yearly pay for principal performance architect in Michigan is $149,376.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,400.00 and $169,500.00 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 Michigan? For Principal Performance Architect jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Principal Performance Architect jobs in Michigan look for? The top searched job categories for Principal Performance Architect jobs in Michigan are:
What cities in Michigan are hiring for Principal Performance Architect jobs? Cities in Michigan with the most Principal Performance Architect job openings:
Principal Performance Architect jobs near you
Infographic showing various Principal Performance Architect job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $149,376 per year, or $71.8 per hour.

Principal AI Engineer

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 4 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

We are seeking a Principal AI Engineer with deep, hands-on experience in Large Language Models (LLMs) to lead the design, development, and deployment of enterprise-grade AI-powered automation systems across the organization.
This role goes beyond experimentation. You will own and deliver production-scale AI solutions, analyze complex internal workflows, identify high-value automation opportunities, and architect intelligent systems that materially improve efficiency, accuracy, and scalability.
This position is ideal for a seasoned engineer (10+ years) who combines strong technical depth, architectural judgment, and a product mindset, and who enjoys building practical, high-impact AI systems used at scale.
KEY RESPONSIBILITIES:
  • Lead the design, development, and deployment of LLM-based automation solutions across multiple business functions.
  • Work closely with cross-functional teams to define problem statements, data requirements, system boundaries, and solution approaches.
  • Architect and implement end-to-end LLM systems, including:
    • Prompt pipelines
    • Agent-based architectures
    • Retrieval-Augmented Generation (RAG) systems
    • Internal AI services and APIs
  • Integrate commercial and open-source LLMs (e.g., OpenAI, Anthropic, Databricks, open-source models) into enterprise systems and products.
  • Drive model evaluation, prompt optimization, and system reliability improvements based on real-world usage.
  • Establish and maintain monitoring, logging, and evaluation frameworks for LLM-driven applications.
  • Partner with product, operations, security, and engineering teams to map workflows and identify high-ROI automation opportunities.
  • Ensure all AI solutions meet enterprise standards for data privacy, security, compliance, and governance.
  • Act as a technical mentor and thought leader, setting best practices for LLM engineering and applied AI.
  • Stay current with advances in LLMs, agent frameworks, AI infrastructure, and applied research-and translate them into pragmatic solutions.

Basic Qualifications:
  • Bachelor's degree in AI, Machine Learning, Computer Science, Statistics, or a related field
  • A minimum of 8 years of professional experience in software engineering, AI, or machine learning, including a minimum of 3 years of significant hands-on work on LLM-based systems.
  • Proven, production experience with Large Language Models, including:
    • Prompt engineering and prompt optimization
    • Model integration and orchestration
    • Evaluation and reliability tuning
  • Strong proficiency in Python and modern AI/ML frameworks and libraries (e.g., PyTorch, TensorFlow, LangChain, similar ecosystems).
  • Solid background in deep learning and applied machine learning.
  • Strong analytical and mathematical foundation relevant to ML systems.
  • Experience designing systems that balance performance, scalability, cost, and accuracy.
  • Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders.
  • Strong written and spoken English.

Preferred Qualifications:
  • Master's degree in AI, Machine Learning, Computer Science, Statistics, or a related field (or equivalent professional experience).
  • PhD or additional advanced degree in AI, Machine Learning, Computer Science, Statistics, or related fields.
  • Experience building meaningful visualizations and explaining model behavior and results.
  • Background in data mining, analytics, or decision-support systems.
  • Experience with regression, supervised and unsupervised learning, and applied ML in production contexts.
  • Prior experience with automotive, IoT, or large-scale industrial data.
  • Contributions to open-source projects or published technical work.
  • Experience operating AI systems under enterprise governance, security, and compliance constraints.

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