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Embedded Ai Engineer Jobs in Wisconsin (NOW HIRING)

The Enterprise AI Enablement Engineer is a new position reporting directly to the CIO. We created ... in an embedded or consulting capacity is a strong differentiator Core Technology Stack • ...

In this role, you will learn to design, develop, test, and integrate embedded software that ... Bring curiosity and enthusiasm for AI-assisted development , exploring responsible ways to use AI ...

WI · On-site

$100 - $130/hr

About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success ... Engineering and CTOs. * Team Enablement & Knowledge Sharing: Contribute reusable POC assets ...

Senior Director - Client Data Solutions

Wauwatosa, WI · Remote

$103K - $139K/yr

Partner with executive stakeholders across Product, AI Engineering, and Client Services to align ... and embedded data experiences. * Deliver scalable, templated reporting solutions that reduce ...

Senior Director - Client Data Solutions

Wauwatosa, WI · On-site +1

$103K - $139K/yr

Partner with executive stakeholders across Product, AI Engineering, and Client Services to align ... and embedded data experiences. * Deliver scalable, templated reporting solutions that reduce ...

Showing results 21-40

Embedded Ai Engineer information

See Wisconsin salary details

$70.7K

$154.8K

$175.6K

How much do embedded ai engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for embedded ai engineer in Wisconsin is $154,818.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,700.00 and $174,600.00 per year, depending on experience, location, and employer.

What is an embedded AI engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

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

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an embedded AI engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.
What are popular job titles related to Embedded Ai Engineer jobs in Wisconsin? For Embedded Ai Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Embedded Ai Engineer jobs in Wisconsin look for? The top searched job categories for Embedded Ai Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Embedded Ai Engineer jobs? Cities in Wisconsin with the most Embedded Ai Engineer job openings:
Infographic showing various Embedded Ai Engineer job openings in Wisconsin as of July 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $154,818 per year, or $74.4 per hour.

Enterprise AI Enablement Engineer

Zywave

Milwaukee, WI

Full-time

Re-posted 16 days ago


Job description

Zywaveis in the middle of a company-wide push to bring AI into how we work, and this role sits at the center of it. The Enterprise AI Enablement Engineer is a new position reporting directly to the CIO. We created it because teams across the businessoftenhave a clear sense of what they want to automate but need a technical partner to help them get there.

This person will work closely with teams throughout the enterprise including Sales, Customer Success, Engineering, Finance, and other areas, moving quickly from a conversation about a problem to a working prototype. The expectation is fast iteration, not perfection. Good and shipped beats perfect and pending.

You will work primarily with Anthropic Claude, TrueFoundry, and a broad set of enterprise tools including Salesforce, Atlassian, and Microsoft 365. This is the first role of its kind at Zywave.

What Makes This Role Different

First, you will not be writing tickets for someone else to build. You will be in the room when a team describes a problem,potentiallybuilding the first version before the meeting ends, and refining it based on real feedback within days. Surfacing the real need behind what someone asks for is just as important as your ability to write the code to solve it.

Second, this is a founding role - the first of its type here. Our success will create growth opportunities for the right candidate.

Core Responsibilities

Work with business stakeholders acrossZywavetoidentifyand prioritize AI automation opportunities, including needs teams have not yet put into words

Turn loosely defined problems into working prototypes, refining them in close collaboration with stakeholders along the way

Build AI-powered workflows, automations, and integrations using Claude,TrueFoundry, and connected MCP tools including Atlassian, Salesforce, Microsoft 365, and many more

Own projects from theinitialconversation through to delivery

Keep security front of mind in every solution you design or deploy, working with the CISO and Security team on risk and compliance requirements

Drive adoption of Claude Chat andCoworkacross the organization through hands-on support anddemonstratedresults

Support teams involved in our citizen developer andvibe codingprograms, includingReplitand Claude Code

Document what works so that patterns and reusable components can be shared across the company

Required Skills and Experience

Discovery and Business Analysis

Proven ability to draw out unstated requirements through both structured and informal conversations with stakeholders

Background in a business analyst, solutions consultant, or similar role with significant client or stakeholder-facing work

Comfortable running working sessions with non-technical audiences at any level of the organization

Able to write clear user stories and lightweight specs quickly, without waiting for a perfect brief

Engineering and Development

Strong working knowledge of Python and/or JavaScript or TypeScript for prototyping and API integration

Hands-on experience with LLM APIs, with Anthropic Claude preferred, including prompt engineering and building agentic workflows

Familiarity with MCP (Model Context Protocol) servers and tool-calling patterns

Experience connecting enterprise SaaS platforms via REST APIs, including tools like Salesforce, Atlassian, and Microsoft Graph

Working knowledge of CI/CD and cloud deployment, with Azure experience preferred

Security Mindset

Understands secure development practices and knowshow to handle sensitive data, credentials, and access controls appropriately

Operates fluently within the org's agent anddata-securityguardrails, exercising independent judgment on routine decisions and partnering with Security Team on novel risk rather than working around it

Experience working within SOC 2 or ISO 27001 environments is a plus

Soft Skills

Comfortable starting work without a fully defined scope

Strong bias toward shipping, with the judgment to know when something needs more time

Clear communicator in writing and in person, whether the audience is a CFO or a frontline user

Able to manage work across multiple teams at the same time without losing track of priorities

Team-oriented and low-ego, with a genuine interest in helping colleagues succeed

Ideal Background

5+years software engineering experience with direct and meaningful stakeholder-facing responsibility

Track recordof shipping AI-powered tools in production environments

Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent experience

Background in SaaSor enterprise software preferred

Prior experience in an embedded or consulting capacity is a strong differentiator

Core Technology Stack

Familiarity with the platforms below is expected. Deepexpertiseacross all of them is not.

Claude (Anthropic)

TrueFoundry(MCP gateway and AI deployment)

Claude Code andCowork

Salesforce, Atlassian (Jira and Confluence), Microsoft 365 and Azure

Replit

Snowflake, GitHub, Slack

Python, JavaScript/TypeScript, REST APIs

Why Work at Zywave?

Zywave empowers insurers and brokers to drive profitable growth and thrive in today's escalating risk landscape. Only Zywave delivers a powerful Performance Multiplier, bringing together transformative, ecosystem-wide capabilities to amplify impact across data, processes, people, and customer experiences. More than 15,000 insurers, MGAs, agencies, and brokerages trust Zywave to sharpen risk assessment, strengthen client relationships, and enhance operations. Additional information can be found at www.zywave.com.

Equal Opportunity Employer

Zywave is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status. We are committed to building an inclusive workplace where everyone can do their best work. If you need a reasonable accommodation during the application or interview process, please contact our Talent Acquisition team.

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