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Generative Ai Testing Jobs in Minnesota (NOW HIRING)

Lead AI Engineer - Observability

Hopkins, MN · On-site

$104K - $137K/yr

Job Summary The Lead Engineer (Generative AI) is a senior technical role responsible for designing ... Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

New

Lead AI Platform Engineer

Minneapolis, MN · On-site

$107K - $140K/yr

Job Summary The Lead Engineer (Generative AI) is a senior technical role responsible for designing ... Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

Lead AI Platform Engineer

Hopkins, MN · On-site

$104K - $137K/yr

Job Summary The Lead Engineer (Generative AI) is a senior technical role responsible for designing ... Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

Lead AI Engineer - Observability

Minneapolis, MN · On-site

$107K - $140K/yr

Job Summary The Lead Engineer (Generative AI) is a senior technical role responsible for designing ... Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

New

Senior AI Engineer

Eden Prairie, MN · On-site

$120 - $160/hr

... Software Testing Services. As a Google Cloud Partner, we excel in Oracle, SAP, and Java ... generative and agentic AI solutions on a multi-cloud, multi-model stack. The ideal candidate is ...

Do you enjoy combining software engineering, analytics, machine learning, and Generative AI to ... testing, documentation, code reviews, and performance optimization. * Communicate analytical ...

Sr AI/ML Engineer - Remote

Minnetonka, MN · On-site +1

$106K - $146K/yr

Ensure high availability, security, and performance of deployed models through rigorous testing ... Experience utilizing generative AI development tools (such as LangChain, Hugging Face, or prompt ...

Sr AI/ML Engineer - Remote

Minnetonka, MN · On-site +1

$106K - $146K/yr

Ensure high availability, security, and performance of deployed models through rigorous testing ... Experience utilizing generative AI development tools (such as LangChain, Hugging Face, or prompt ...

Enable Generative AI use cases includingLLMs, RAG, embeddings, vector search, and agentic ... Apply strong engineering practices including automated testing, CI/CD, infrastructure automation ...

Showing results 21-40

Generative Ai Testing information

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in Minnesota?

For Generative Ai Testing jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Minnesota look for?

The top searched job categories for Generative Ai Testing jobs in Minnesota are:

What cities in Minnesota are hiring for Generative Ai Testing jobs?

Cities in Minnesota with the most Generative Ai Testing job openings:

Infographic showing various Generative Ai Testing job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution.

Lead AI Engineer - Observability

US Bank

Hopkins, MN • On-site

$104K - $137K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


U.S. Bank rating

8.1

Company rating: 8.1 out of 10

Based on 364 frontline employees who took The Breakroom Quiz

67th of 175 rated banks


Job description

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at-all from Day One.

Job Description

Job Summary

The Lead Engineer (Generative AI) is a senior technical role responsible for designing, developing, and operationalizing enterprise-scale Generative AI (GenAI) solutions. This position combines deep hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI architectures with strong technical leadership to deliver secure, scalable, and resilient AI systems.

The role partners across engineering, product, and business teams to translate complex requirements into production-ready AI capabilities aligned with enterprise standards for security, risk, and responsible AI.

Key Responsibilities

1. GenAI Solution Engineering

  • Design, develop, and deploy GenAI solutions leveraging:

    • Large Language Models (LLMs)

    • Retrieval-Augmented Generation (RAG) architectures

    • Prompt engineering techniques

    • Agentic AI workflows and orchestration

  • Build intelligent systems using frameworks such as LangChain, LangGraph, AWS Bedrock, and Microsoft Foundry Agent Service

  • Evaluate emerging tools and frameworks to continuously improve solution quality and innovation

2. GenAIOps & Lifecycle Management

  • Lead the end-to-end lifecycle of GenAI solutions, including:

    • Solution architecture and engineering

    • Integration with enterprise systems

    • Secure deployment and release management

    • Monitoring, observability, and continuous optimization

  • Implement GenAIOps best practices to ensure scalability, reliability, and cost efficiency

  • Establish logging, evaluation, and feedback mechanisms for production AI systems

3. Cloud, Platform & Scalability Engineering

  • Architect and deploy GenAI applications across cloud environments (Azure and AWS)

  • Design distributed systems capable of supporting high-throughput, low-latency AI workloads

  • Leverage modern infrastructure practices:

    • Containerization (Docker)

    • Orchestration (Kubernetes)

    • Infrastructure as Code (Terraform, ARM/Bicep)

  • Ensure high availability, performance, and enterprise-grade security

4. Software Engineering & Architecture

  • Develop scalable, maintainable applications using Python and microservices-based architectures

  • Apply secure coding standards and robust data handling practices for regulated environments

  • Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

  • Enforce engineering best practices including code reviews, testing, and documentation

5. Technical Leadership & Influence

  • Provide architectural leadership and guidance across GenAI initiatives

  • Drive critical design decisions for large-scale, complex AI solutions

  • Mentor and coach senior engineers and development teams

  • Translate business requirements into scalable, secure, and resilient technical solutions

  • Partner with stakeholders across product, business, risk, and security functions

Basic Qualifications

  • Bachelor's degree, or equivalent work experience

  • Six to eight years of relevant experience

Experience Should Include

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field

  • 8+ years of experience in software engineering, platform engineering, or AI/ML solutions

  • 2+ years hands-on experience with GenAI technologies, including LLMs and RAG architectures and vector databases

  • Strong knowledge of agentic AI concepts and frameworks (e.g., LangChain, LangGraph)

  • Experience with cloud platforms (Azure and/or AWS)

  • Deep understanding of distributed systems and scalable architecture patterns

  • Proficiency in Python and microservices-based development

  • Experience with Docker, Kubernetes, and Infrastructure as Code tools

  • Demonstrated technical leadership and mentoring experience

Preferred Qualifications

  • Experience implementing GenAI solutions in enterprise or regulated environments

  • Familiarity with observability frameworks and AI lifecycle tooling

  • Understanding of AI governance, security, and compliance requirements

  • Experience contributing to or working with AI/ML or GenAI frameworks

  • Background in financial services or other highly regulated industries

Core Competencies

Technical Depth & Innovation

  • Strong expertise in GenAI architectures and evolving AI technologies

  • Ability to balance experimentation with enterprise-grade reliability

Architecture & Systems Thinking

  • Designs scalable, distributed, and resilient systems

  • Aligns architecture decisions with enterprise standards and long-term strategy

Execution & Operational Excellence

  • Drives end-to-end delivery from concept through production

  • Ensures high standards for quality, security, and performance

Leadership & Collaboration

  • Influences without authority and leads through technical expertise

  • Mentors engineers and elevates overall team capability

Business & Stakeholder Alignment

  • Translates complex technical concepts into business outcomes

  • Partners effectively across product, engineering, and leadership teams

***This role requires working from a U.S. Bank location three (3) or more days per week.***

If there's anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to ourdisability accommodations for applicants.

Benefits:

Our approach to benefits and total rewards considers our team members' whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following:

  • Healthcare (medical, dental, vision)

  • Basic term and optional term life insurance

  • Short-term and long-term disability

  • Pregnancy disability and parental leave

  • 401(k) and employer-funded retirement plan

  • Paid vacation (from two to five weeks depending on salary grade and tenure)

  • Up to 11 paid holiday opportunities

  • Adoption assistance

  • Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

Review our full benefits available by employment status here.

U.S. Bank is an equal opportunity employer. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, and other factors protected under applicable law.

E-Verify

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about theE-Verify program.

The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements). Pay Range: $139,230.00 - $163,800.00

U.S. Bank will consider qualified applicants with arrest or conviction records for employment. U.S. Bank conducts background checks consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act as well as the San Francisco Fair Chance Ordinance. U.S. Bank is subject to, and conducts background checks consistent with the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA). In addition, certain positions may also be subject to the requirements of FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or federal guidelines applicable to an agreement, such as those related to ethics, safety, or operational procedures.

Applicants must be able to comply with U.S. Bank policies and procedures including the Code of Ethics and Business Conduct and related workplace conduct and safety policies.

Posting may be closed earlier due to high volume of applicants.


What U.S. Bank employees say

Pay

Benefits

Hours and flexibility

Workplace

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About U.S. Bank

Sourced by ZipRecruiter

U.S. Bank is a reputable and established financial institution that plays a significant role in the banking sector. With a history spanning over 150 years, U.S. Bank has built a strong foundation of trust and reliability. As a comprehensive bank, they offer a wide array of financial products and services to cater to the diverse needs of their customers, including individuals, businesses, and communities. Customer satisfaction is of utmost importance to U.S. Bank. They prioritize delivering exceptional service and fostering long-term relationships with their clients. Through their extensive network of branches and advanced digital banking platforms, U.S. Bank ensures convenient access to their services, empowering customers to manage their finances efficiently and securely.

Industry

Banking and credit intermediation

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

Year founded

1863

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