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Ai Rag Jobs in Detroit, MI (NOW HIRING)

You are a hybrid architect developer who excels at translating complex AI concepts-such as Agentic workflows, orchestration patterns, and RAG architectures-into "Golden Path" reference ...

Practice Manager - AI & Data

Troy, MI ยท On-site

$160K - $190K/yr

Generative AI & LLM ecosystems (prompt engineering, RAG, multi-agent systems) * Data Engineering & Modern Data Platforms (ETL/ELT, streaming, data lakes, data mesh) * Cloud-based AI architectures ...

Practice Manager - AI & Data

Troy, MI ยท On-site

$160K - $190K/yr

Generative AI & LLM ecosystems (prompt engineering, RAG, multi-agent systems) * Data Engineering & Modern Data Platforms (ETL/ELT, streaming, data lakes, data mesh) * Cloud-based AI architectures ...

Practice Manager - AI & Data

Troy, MI ยท On-site

$160K - $190K/yr

Generative AI & LLM ecosystems (prompt engineering, RAG, multi-agent systems) * Data Engineering & Modern Data Platforms (ETL/ELT, streaming, data lakes, data mesh) * Cloud-based AI architectures ...

Implement retrieval-augmented generation (RAG) architectures using internal and external data ... Ensure responsible AI practices, including privacy, security, and bias mitigation * Rapidly ...

Implement retrieval-augmented generation (RAG) architectures using internal and external data ... Ensure responsible AI practices, including privacy, security, and bias mitigation * Rapidly ...

You are a hybrid architect developer who excels at translating complex AI concepts-such as Agentic workflows, orchestration patterns, and RAG architectures-into "Golden Path" reference ...

Showing results 41-60

Ai Rag information

See Detroit, MI salary details

$31.7K

$57.7K

$82.7K

How much do ai rag jobs pay per year?

As of Sep 12, 2026, the average yearly pay for ai rag in Detroit, MI is $57,661.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $64,300.00 per year, depending on experience, location, and employer.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What are popular job titles related to Ai Rag jobs in Detroit, MI?

For Ai Rag jobs in Detroit, MI, the most frequently searched job titles are:

What cities near Detroit, MI are hiring for Ai Rag jobs?

Cities near Detroit, MI with the most Ai Rag job openings:

AI Software Test Engineer (SDET) [211341]

Ann Arbor, MI โ€ข On-site

Aquent Talent
Recruiting and Staffing Servicesย โ€ขย 51 - 200 employees

$42.06 - $46.73/hr

Temporary

Medical, Dental, Vision, Retirement

Re-posted 8 days ago


Key responsibilities

  • Own the end-to-end testing and automation efforts for AI solutions.

  • Validate AI model outputs for accuracy, consistency, reliability, and safety through various testing methods.

  • Design and execute functional, integration, end-to-end, regression, and performance tests specifically for AI solutions.


Job description

Partnering with Aquent, we are thrilled to represent a leading organization at the forefront of financial innovation. This institution is dedicated to building secure, reliable, and cutting-edge solutions that empower millions of users to achieve their financial goals. Join a team that is shaping the future of technology within the financial industry, driving impact through advanced engineering and a commitment to excellence.

Are you ready to dive into the exciting world of Artificial Intelligence and make a tangible impact on the next generation of intelligent systems? This pivotal role offers a unique opportunity to spearhead the quality assurance of groundbreaking AI-powered applications, machine learning systems, AI agents, and generative AI solutions. You will be instrumental in ensuring that our AI systems are not just innovative, but also reliable, safe, accurate, and performant, directly contributing to the trust and success of our advanced technology initiatives and the millions of users we serve.

About the Role and Your Impact

As a critical contributor, you will own the end-to-end testing and automation efforts for robust AI solutions. Youโ€™ll collaborate closely with AI developers, architects, and product teams to guarantee production-quality AI, directly reducing regression defects, improving confidence in AI model behavior, and enabling the safe, scalable delivery of AI-powered features. This role offers significant opportunities for innovation and collaboration across diverse teams, directly shaping the reliability and success of cutting-edge AI technologies that meet stringent quality, security, and governance requirements.

Key Responsibilities

  • Develop and implement comprehensive testing strategies for AI applications, platforms, and services.
  • Validate AI model outputs for accuracy, consistency, reliability, and safety, performing adversarial, negative, and edge-case testing to identify potential failures and hallucinations.
  • Design and execute functional, integration, end-to-end, regression, and performance tests specifically tailored for AI solutions.
  • Create intricate test cases for prompt-driven, agentic, and retrieval-based AI workflows, ensuring robust validation of AI guardrails, business rules, permissions, and governance controls.
  • Build and maintain advanced automated test frameworks and evaluation pipelines for AI responses and workflows, integrating AI testing seamlessly into continuous integration/continuous delivery (CI/CD) pipelines.
  • Implement automated quality scoring and regression detection mechanisms, and create reusable test data, mocks, simulators, and validation frameworks.
  • Test AI agents, workflows, APIs, complex system integrations, and tool-calling capabilities, validating integrations with external systems, data sources, and enterprise services.
  • Verify performance, reliability, scalability, and resiliency of AI workloads, including executing load and stress testing for AI services.
  • Collaborate proactively with software engineers, AI engineers, product owners, architects, and security teams, providing critical quality feedback during design reviews and development.
  • Contribute significantly to test strategy, quality standards, and best practices, and support production readiness reviews and defect triage activities.
  • Contribute to projects such as testing AI chat assistants and copilots, validating AI agent workflows, evaluating retrieval augmented generation (RAG) search quality, automating AI response evaluation frameworks, and performance testing AI services and orchestration platforms.

Must-Have Qualifications

  • Bachelorโ€™s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
  • 3โ€“6 years of experience in software testing, QA automation, or quality engineering.
  • Proven experience developing automated test solutions using Python, Java, JavaScript/TypeScript, or C#.
  • Demonstrated experience with API testing and automation tools.
  • Strong understanding of test automation principles, the Software Development Lifecycle (SDLC), Agile methodologies, and CI/CD pipelines.
  • Experience testing distributed systems, web applications, and APIs.
  • Proficiency in AI Testing concepts including Prompt Testing, Response Evaluation, Hallucination Detection, Agent Workflow Validation, RAG Validation, AI Safety Testing, AI Regression Testing, and AI Benchmarking.
  • Expertise in Quality Engineering practices such as Test Automation, API Testing, Integration Testing, Performance Testing, Load Testing, Security Testing, Defect Analysis, and Root Cause Investigation.
  • Familiarity with industry-standard tools and technologies like Selenium, Playwright, Postman, JUnit / PyTest, GitHub Actions, Jenkins, Docker, and Kubernetes.

Nice-to-Have Qualifications

  • 1-3 years of exposure to AI/ML or Generative AI technologies.
  • Experience testing Generative AI applications, large language model (LLM)-based systems, AI agents, RAG applications, or complex platform integrations.
  • Familiarity with leading AI models and platforms.
  • Experience building evaluation and benchmarking frameworks for AI solutions.
  • Experience testing cloud-native applications on major cloud platforms.
  • Knowledge of responsible AI, AI governance, and AI risk management practices, understanding how AI initiatives align with enterprise governance, risk, privacy, and compliance requirements.

About Aquent Talent

Aquent Talent connects the best talent in marketing, creative, and design with the worldโ€™s biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. We also offer free online training through Aquent Gymnasium. More information on our awesome benefits!

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. Weโ€™re about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.

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