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Ai Integration Jobs in Fox Point, WI (NOW HIRING)

AI Developer

Milwaukee, WI · On-site

$53.75 - $71/hr

Applies AI and Technology Identifies opportunities to boost efficiency and add value using AI and ... Eagerly learns and integrates new technologies where they matter most. * Champions Innovation ...

Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...

Senior Software Engineer

Milwaukee, WI · On-site

$120K - $158K/yr

Required : • 5+ years of software development experience, including 2+ years working on AI-powered applications or AI-integrated solutions. • Bachelor's degree in Computer Science, Computer ...

Technical expertise in AI integration across natural language processing, computer vision, and generative models. What You'll Do and Impact: * Lead and mentor engineers in AI-first development ...

Senior Software Engineer

Milwaukee, WI · On-site

$120K - $159K/yr

Technical expertise in AI integration across natural language processing, computer vision, and generative models. What You'll Do and Impact: * Lead and mentor engineers in AI-first development ...

Senior Software Engineer

Milwaukee, WI · On-site

$120K - $159K/yr

Technical expertise in AI integration across natural language processing, computer vision, and generative models. What You'll Do and Impact: * Lead and mentor engineers in AI-first development ...

Senior Software Engineer

Milwaukee, WI · On-site

$120K - $159K/yr

Technical expertise in AI integration across natural language processing, computer vision, and generative models. What You'll Do and Impact: * Lead and mentor engineers in AI-first development ...

Responsibilities : • Define and execute the AI engineering strategy, embedding AI-first principles across teams and projects. • Architect and scale AI-enhanced systems, integrating LLMs, agentic ...

Technical expertise in AI integration across natural language processing, computer vision, and generative models. * Experience in architecting scalable AI-powered solutions that align with long-term ...

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Ai Integration information

See Fox Point, WI salary details

$19.8K

$108.5K

$157.2K

How much do ai integration jobs pay per year?

As of Aug 19, 2026, the average yearly pay for ai integration in Fox Point, WI is $108,458.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,700.00 and $134,700.00 per year, depending on experience, location, and employer.

What is AI integration?

AI integration refers to the process of incorporating artificial intelligence technologies into existing systems, applications, or business processes to enhance automation, improve decision-making, and optimize performance. This can involve connecting AI models, such as machine learning algorithms or natural language processing tools, with software platforms, databases, or workflows. The goal is to enable systems to analyze data, learn from patterns, and perform tasks that traditionally required human intelligence. AI integration can benefit a wide range of industries, including healthcare, finance, manufacturing, and customer service.

What are some common challenges faced when integrating AI solutions into existing business processes?

One of the most common challenges in AI integration is ensuring that new AI tools seamlessly interact with legacy systems and data formats. Team members often need to address data quality issues, adapt workflows, and manage stakeholder expectations regarding the capabilities and limitations of AI. Collaboration with IT, operations, and business units is essential to customize solutions and ensure user adoption. Additionally, ongoing monitoring and retraining of AI models is necessary to maintain performance and align with evolving business goals.

What are the key skills and qualifications needed to thrive as an AI integration specialist, and why are they important?

To excel as an AI Integration Specialist, you need a solid background in computer science, proficiency in programming languages (such as Python), and experience with machine learning frameworks, often supported by a relevant degree or certifications. Familiarity with cloud platforms (like AWS, Azure, or Google Cloud), APIs, and integration tools is typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams make someone stand out in this role. These competencies are crucial for successfully implementing AI solutions that align with business needs and ensuring seamless system interoperability.

What is the difference between Ai Integration vs Data Analyst?

AspectAi IntegrationData Analyst
Required CredentialsBachelor's in Computer Science, Engineering, or related fields; knowledge of AI/ML toolsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI development teams, software firmsBusiness, finance, healthcare, and other industries analyzing data
Employer & Industry UsageDeveloping AI solutions, integrating AI into productsInterpreting data, generating reports, supporting decision-making

While Ai Integration specialists focus on implementing AI systems and integrating AI technologies into applications, Data Analysts interpret data to provide insights and support business decisions. Both roles require analytical skills, but Ai Integration emphasizes technical development and system integration, whereas Data Analysts focus on data interpretation and reporting.

How to get into AI integration?

To pursue a career in AI integration, develop skills in programming languages like Python, understand machine learning frameworks, and gain experience with AI tools and APIs. Earning relevant certifications and working on projects that demonstrate AI implementation can improve job prospects.

Principal Technical Product Manager - AI Integration

Cotality

Milwaukee, WI • On-site

Full-time

Medical, Life, Retirement, PTO

Posted 25 days ago


Job description

At Cotality, we are driven by a single mission-to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

Role Summary

The Principal Technical Product Manager for AI Integration owns the strategy and delivery of Cotality Insurance's external-facing AI integration layer. This includes the MCP server ecosystem, AI/API gateway, developer experience, and the platform that enables AI agents from clients and third-party partners to discover, authenticate, and consume Cotality's insurance data products autonomously.

This is a technical product leadership role with a player-coach model. You set the product direction, make architecture tradeoff decisions alongside Architecture, and drive execution through a dedicated engineering team and cross-functional application team partners who own the underlying product APIs.

Core Responsibilities

MCP Platform Strategy & Roadmap. Define which Cotality data products get exposed as MCP tools, in what order, and with what capabilities. Align the connector roadmap with business priorities across Claims, Underwriting, Catastrophe Risk, and Contractor Solutions. Own the sequencing decisions - what ships this quarter, what's next, and why. Target cadence: one new MCP connector live per month.

Tool Schema & Data Product Definition. Partner with product teams and the Data Architect to define what data gets exposed through each MCP tool - the fields, the boundaries, the descriptions that AI agents read to decide when and how to use a tool. This is the highest-leverage work in the role. The quality of tool schemas directly determines whether an AI agent can use Cotality's data effectively or makes errors that damage client trust.

Architecture & Technical Direction. Work with the Architect and engineering team to define gateway configurations, authentication flows, and the aggregation layer. Make tradeoff decisions - when to optimize for speed vs. extensibility, when to wrap an existing API vs. build a composite tool, when to ship and iterate vs. get it right the first time. You don't write the code, but you understand the architecture deeply enough to lead technical decisions.

Developer Experience. Own the end-to-end experience for external developers and AI platforms integrating with Cotality's MCP endpoints. This includes the developer portal, API documentation, sandbox environments, authentication guides, SDK examples, and onboarding workflows. You understand what good developer experience feels like because you've been the developer - you've integrated against third-party APIs, read bad documentation, and know the difference between a portal that accelerates adoption and one that generates support tickets. Target: a developer or AI agent goes from zero to working Cotality data in under 60 minutes.

Data Provenance & Trust. Own the strategy for ensuring data delivered through MCP tools is verifiable, auditable, and resistant to misattribution or hallucination by consuming AI agents. Define response metadata standards, logging requirements, and the guardrails that protect Cotality's brand when data flows through systems Cotality doesn't control. This includes near-term controls (response signing, audit logs, server instructions) and the longer-term innovation roadmap for data provenance.

Go-to-Market Coordination. Work with product marketing, sales engineering, and business development to position the MCP platform for carrier clients and AI platform partners. Support demos, pilot programs, and partner integrations.

Cross-Functional Execution. Drive delivery through a dedicated MCP engineering team (MCP Architect, MCP Engineers, Data Architect) and application team partners who own the underlying product APIs. You define what needs to be built, set priorities, and shape tool designs. Application teams contribute significant implementation effort, particularly around exposing their product APIs as MCP-ready services. Keeping multiple workstreams aligned and moving toward shared delivery timelines is a core part of the role.

Job Qualifications:

Required
  • 8+ years in technical product management or architecture, with at least 3 years owning API platforms, developer tools, data products, or integration infrastructure
  • Engineering background - you've written code professionally and carry an intuitive understanding of what makes a great developer experience from the consumer side, not just the provider side
  • Demonstrated experience shipping developer-facing or machine-consumable products with measurable adoption metrics
  • Strong understanding of API gateway patterns, OAuth/authentication flows, and how distributed systems communicate
  • Working knowledge of how large language models consume tools - function calling, tool descriptions, context windows, and the failure modes that arise when AI agents interact with external data sources
  • Experience defining data products for external consumption - what to expose, what to withhold, how to structure responses for different consumer types, and how to manage data quality and trust
  • Track record of driving delivery through cross-functional teams without direct reporting authority - influencing engineering, product, and business stakeholders to execute against a shared roadmap
  • Exceptional written communication - you will write tool descriptions that AI agents read, developer documentation that humans read, strategy documents that leadership reads, and contract language that legal reviews
  • Comfort with ambiguity and speed - this is a new category with no playbook, requiring decisions with incomplete information, shipping MVPs, and iterating rapidly
Preferred
  • Experience with specific API gateway technologies (Apigee, Kong, AWS API Gateway, or equivalent)
  • Hands-on experience with developer documentation and portal platforms - Mintlify, Swagger/OpenAPI, Redoc, ReadMe, or similar - and a strong opinion on what makes API documentation actually usable
  • Familiarity with the Model Context Protocol (MCP) or equivalent agent-tool interface standards
  • Experience in insurance, financial services, or regulated data industries
  • Understanding of data provenance, audit requirements, and compliance considerations in regulated environments
  • Experience with pricing and packaging of API/data products (per-query, tiered access, usage-based models)
  • Background in or exposure to AI/ML workflows, particularly how enterprises are deploying AI agents in production
What Differentiates the Ideal Candidate

This role is not about managing a backlog and writing user stories. The ideal candidate is someone who thinks about how machines consume data - not just how humans use software. They understand that a tool description is an instruction set for an LLM, that a missing field in an API response can trigger hallucination in an agent, and that the developer experience for an AI platform partner looks fundamentally different from the developer experience for a human integration engineer.

They are comfortable being the bridge between deeply technical architecture discussions and business strategy conversations. They can explain to an engineer why a tool schema needs to be restructured for agent effectiveness, and they can explain to a VP of Sales why a carrier's AI agent using Cotality data is a stickier revenue relationship than a traditional API integration.

They see the opportunity: agent-consumable insurance intelligence is a new product category, and the person in this role gets to define it.

Annual Pay Range:

111,900 - 175,000 USD

Application Window:

This opportunity is expected to remain posted through the date identified below, subject to business needs.

Thrive with Cotality

At Cotality, we offer more than just a job, we provide a benefits experience designed to support your whole self. From a flexible working model to competitive time off and standout health coverage with meaningful perks and growth opportunities, our package is built to help you thrive at work and in life.

Highlights, depending on role classification, include:

  • Time off: Generous PTO and 11 paid holidays, plus well-being and volunteer time off.

  • Family Support: Up to 16 weeks of fully paid parental leave and a baby stipend.

  • Health: Multiple medical plan options with mental health and wellness support offerings.

  • Retirement: 401(k) with company match and vesting after one year.

  • Financial Perks: $400 annual well-being stipend and tuition assistance up to $5,250.

  • Extras: Recognition Rewards, Referral bonuses, exclusive discounts and more!

Cotality is an Equal Opportunityemployer committed to attracting and retaining thebest-qualified people available, without regard torace, color, religion, national origin, gender, sexualorientation, gender identity, age, disability or statusas a veteran of the Armed Forces, or any other basisprotected by federal, state or local law. Cotalitymaintains a Drug-Free Workplace.

Cotality is fully committed to a work environment that embraces everyone's uniquecontributions, experiences and values. We offer anempowered work environment that encouragescreativity, initiative and professional growth andprovides a competitive salary and benefits package. We are better together when we support and recognize our differences.

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