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Ai Applications Engineer Jobs in Minnesota (NOW HIRING)

Data Architect & AI Engineer - Microsoft Fabric We are seeking a Data Architect / AI Engineer to ... Ensure data from ERP and other enterprise applications is accurately modeled to reflect business ...

... applications in a cloud environment (Azure preferred). o Strong SQL required and data engineer skills would be a plus. · Technical Skills: o Solution Design skills: Design robust AI solution ...

AI Engineer

Minneapolis, MN · On-site

$50K - $112K/yr

... applications - Managing data quality and infrastructure to support reliable AI operations - Engaging in continuous learning to adapt to new technologies and methodologies in AI engineering What You ...

... protecting AI applications and platforms * Identify emerging AI‑specific threats, attack ... Partner with engineering teams to validate secure deployment patterns for AI workloads across cloud ...

AI Developer

Saint Paul, MN · On-site

$125 - $135/hr

Lead the design and development of advanced AI applications, contributing directly to coding ... Mentor senior engineers and AI practitioners, strengthen technical hiring and onboarding efforts ...

Cloud/AI Engineer

Virginia, MN · On-site

$150 - $230/hr

... applications, and implementing Generative AI capabilities including Large Language Models (LLMs ... Establish and promote architecture, engineering, security, and software development best practices ...

Senior AI Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

Our team of seasoned engineers, designers, and strategists work across industries to create AI applications that actually get used and make a difference. The Role You're a technical leader who shapes ...

Showing results 21-40

Ai Applications Engineer information

What is an AI applications engineer?

AI Applications Engineers are professionals who design, develop, and integrate artificial intelligence (AI) solutions into software applications to solve real-world problems. They work closely with data scientists, software engineers, and business stakeholders to build and deploy machine learning models, automate processes, and enhance user experiences. Their responsibilities often include selecting appropriate AI technologies, writing code, testing models, and optimizing performance. AI Applications Engineers play a key role in translating AI research and prototypes into scalable and maintainable products used in industries like healthcare, finance, retail, and more.

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

To thrive as an AI Applications Engineer, you need strong programming abilities (Python, Java, or C++), a solid understanding of machine learning algorithms, and a relevant degree in computer science or engineering. Familiarity with AI frameworks (such as TensorFlow or PyTorch), cloud platforms, and data processing tools is typically required, along with certifications in machine learning or AI. Excellent problem-solving, collaboration, and communication skills help you translate business needs into effective AI solutions and work efficiently with cross-functional teams. These skills are critical for building scalable, reliable AI systems that deliver tangible value to organizations.

How does an AI applications engineer typically collaborate with data scientists and software developers on project teams?

As an AI Applications Engineer, you will often serve as a bridge between data scientists, who build and optimize machine learning models, and software developers, who integrate these models into production systems. Collaboration usually involves translating model requirements into scalable application features, ensuring model outputs align with user needs, and troubleshooting technical challenges that arise during deployment. Regular meetings, code reviews, and shared documentation are common practices to keep everyone aligned and ensure seamless integration. This cross-functional teamwork enhances both the technical robustness and usability of AI-powered applications.

What is the difference between Ai Applications Engineer vs Data Scientist?

AspectAi Applications EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI/ML toolsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI solutions, collaborates with engineering teamsAnalyzes data, builds models, interprets results
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, tech, research institutions

While both roles involve AI and data, Ai Applications Engineers focus on developing and deploying AI solutions in engineering contexts, whereas Data Scientists analyze data to extract insights. The roles often overlap but differ mainly in their primary focus and application environment.

What does an AI applications engineer do?

An AI applications engineer designs, develops, and implements artificial intelligence solutions to solve specific business problems. They work with machine learning models, data processing, and programming tools like Python or TensorFlow, often collaborating with data scientists and software developers to deploy AI systems effectively.

What are popular job titles related to Ai Applications Engineer jobs in Minnesota?

For Ai Applications Engineer jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Ai Applications Engineer jobs in Minnesota look for?

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What cities in Minnesota are hiring for Ai Applications Engineer jobs?

Cities in Minnesota with the most Ai Applications Engineer job openings:

Data Arch/AI Engineer

ESP IT

Eden Prairie, MN • On-site

Full-time

Posted 11 days ago


Job description

Job Description Data Architect & AI Engineer - Microsoft Fabric We are seeking a Data Architect / AI Engineer to help build and evolve our modern data and AI ecosystem, with Microsoft Fabric serving as the core data platform. This role will initially play a key part in the migration from legacy reporting and data systems into Microsoft Fabric, ensuring that critical business processes and data are accurately represented in a scalable, governed architecture. Beyond the migration, this individual will help establish the technical foundation, standards, and capabilities needed to expand the organization's use of analytics, automation, and artificial intelligence.

This role will also partner closely with business stakeholders, technical teams, and third-party contractors. They will help ensure the organization has a trusted data foundation while identifying and developing opportunities to leverage AI to improve how the business accesses information, makes decisions, and operates. This is a hands-on role for someone who can move between architecture, engineering, and technical consultation and enjoys translating business challenges into scalable data and AI solutions.

This is a hybrid position based in Eden Prairie, MN. Key Responsibilities Lead and support the transition from legacy data and reporting environments into Microsoft Fabric, helping establish a scalable, governed, and future-ready data foundation. Partner with business stakeholders, technical teams, and third-party contractors to design, validate, and extend data models, pipelines, integrations, and analytical solutions.

Ensure data from ERP and other enterprise applications is accurately modeled to reflect business processes and reporting needs. Design and maintain data architecture and integration patterns that support analytics, Power BI, automation, and emerging AI applications. Establish and evolve the organization's AI technical foundation, identifying and prioritizing practical AI opportunities that deliver measurable business value.

Architect, prototype, and implement AI-enabled solutions using enterprise data, including LLMs, AI APIs, agents, Microsoft/Azure AI capabilities, and other emerging technologies. Help move successful AI concepts from proof of concept into secure, scalable, production-ready solutions. Translate business requirements and complex data questions into effective technical solutions, engaging appropriate business and technical subject-matter experts when needed.

Establish data and AI governance practices that support accuracy, security, integrity, lineage, compliance, and responsible AI adoption. Enable trusted self-service analytics through Microsoft Fabric and Power BI, including development of reusable data models and clearly defined business metrics. Review existing and proposed data and AI solutions, recommending improvements to scalability, maintainability, performance, security, and overall architecture.

Develop documentation, standards, and training to help technical and business users effectively leverage the organization's data and AI capabilities. Serve as a technical bridge between business stakeholders, technology teams, contractors, and leadership, ensuring solutions remain aligned with business priorities. Required Qualifications Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent professional experience.

5-7+ years of experience in data architecture, data engineering, analytics engineering, software engineering, or related technical roles. Strong experience with the Microsoft data ecosystem, ideally including Microsoft Fabric, Azure, Power BI, and related technologies. Experience designing and maintaining enterprise data architectures, data models, integrations, and pipelines.

Working knowledge of SQL and Python; familiarity with Power BI and other analytics or development tools. Experience working with LLM APIs, generative AI platforms, or AI tool deployment in a business environment. Ability to evaluate business problems and determine appropriate data architecture, integration, analytics, or AI solutions.

Strong analytical and problem-solving skills with the ability to independently research complex technical and data questions. Demonstrated ability to work across business and technical teams and communicate effectively with both audiences. Experience reviewing technical designs and providing recommendations around scalability, maintainability, security, and performance.

Preferred Qualifications Hands-on experience implementing or administering Microsoft Fabric in an enterprise environment. Experience with Azure AI services, Azure OpenAI, Microsoft Copilot, or similar enterprise AI technologies. Experience building AI applications using enterprise data, including retrieval-augmented generation (RAG), AI agents, semantic search, or related patterns.

Experience with data governance, lineage, security, compliance, and enterprise data-management standards. Experience moving AI prototypes or proofs of concept into production environments. Impact This role will play an important part in shaping the organization's next generation of data and AI capabilities.

The successful candidate will: Establish Microsoft Fabric as a trusted, scalable enterprise data foundation. Modernize legacy data and reporting architecture while reducing technical debt and improving access to trusted information. Create governed, reusable data assets that support reporting, analytics, automation, and AI.

Help move the organization from experimentation with AI toward practical, production-ready AI solutions. Identify and deliver AI use cases that improve decision-making, productivity, knowledge access, and business processes. Strengthen collaboration between business and technology teams by ensuring data and AI solutions are technically sound and aligned with business priorities.

Build the architecture and standards needed to support the organization's broader digital and AI transformation.