AI Engineer (Org Wide) at Lakeland Care Plus INC

Fond Du Lac, Wisconsin, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Oct, 26

Salary

0.0

Posted On

18 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Microsoft Copilot Studio, Azure AI Foundry, Retrieval-Augmented Generation (RAG), Python, SQL, Power Platform, Azure AI Search, Data Engineering, HIPAA Compliance, Prompt Engineering, MLOps, Microsoft Purview, PowerShell, KQL, Vector Stores, Responsible AI

Industry

Business Consulting and Services

Description

Description Join our award winning culture! Under the supervision of the IT Operations Manager, the AI Engineer is a hands-on builder responsible for designing, deploying, and operating artificial intelligence solutions across LC Plus Technology's client portfolio. The role builds retrieval-grounded agents in Microsoft Copilot Studio and Azure AI Foundry, designs the data ingestion and integration patterns that make those agents reliable, and partners with client compliance, project management, and data analytics functions to ensure every solution respects the regulated environments in which the clients of LC Plus Technology operate. The engineer joins a small, focused technical team and is the voice on AI build feasibility across client conversations. The role mentors peers on Microsoft AI build practices, operates LC Plus Technology's AI Solution Inventory, and stays current on Microsoft's AI platform evolution so it can be translated into client roadmap implications. Initial focus for this role is anchored on managed care client work, with the scope expanding across the client portfolio over time. Essential Competencies: Own design, build, deployment, and operation of AI solutions from intake through production retirement. Maintain audit-readiness, security posture, and data integrity in every implementation. Document architecture decisions, data lineage, evaluation results, and operational runbooks. Translate business problems into solution architectures grounded in data quality, retrieval design, and governance. Evaluate when to apply Copilot Studio versus Azure AI Foundry versus traditional automation, with rationale tied to need and risk. Surface data foundation gaps before agent build, naming dependencies and risks proactively. Deliver solutions with rigorous validation, monitoring, rollback paths, and source citation. Treat every production AI capability as accountable software, not an experiment. Maintain high standards for grounding quality, prompt control, and output reliability. Collaborate with client compliance, project management, data, and business unit stakeholders to align solutions with operational reality. Translate technical constraints into plain language for non-technical stakeholders, including client executive leadership. Identify when to push back on a use case and when to find a path forward. Work effectively with LC Plus Technology peers, client partner functions, external consulting partners, and vendor representatives. Support onboarding of new use cases through client intake processes. Mentor LC Plus Technology peers and client counterparts on Microsoft AI build practices. Demonstrate commitment to the LC Plus Technology mission and to the client-first ethic in technical work. Uphold the consistency and accountability standard expected of all solutions that serve clients and the populations they serve. Operate with full HIPAA and BAA discipline within regulated client environments. Requirements Bachelor's degree in Computer Science, Data Engineering, Information Systems, Health Informatics, or a related discipline, or equivalent professional experience. Five or more years of software engineering or data engineering experience, with at least three years delivering AI or machine learning solutions into production. Demonstrable hands-on experience designing, building, and shipping AI agents in Microsoft Copilot Studio (shipped solutions, not workshop exercises). Hands-on experience with Azure AI Foundry, including project structure, model deployment, evaluation, and monitoring. Hands-on experience implementing retrieval-augmented generation (RAG) patterns, including vector stores (Azure AI Search, Cosmos DB Vector, or comparable), embedding models, chunking strategies, grounding, and source citation. Strong data engineering foundation: experience with data warehousing or lakehouse patterns, ingestion and transformation pipelines, data validation, and lineage practices in Azure SQL, Synapse, Microsoft Fabric, Power BI dataflows, or comparable platforms. Demonstrated proficiency in Microsoft modern workplace governance: Microsoft Purview Data Loss Prevention, Microsoft Entra ID, Conditional Access, Microsoft Graph API, and Managed Environments for Power Platform. Strong working knowledge of Microsoft Power Platform: Power Automate, Power Apps, custom connectors, AI Builder, and Power Platform DLP policies. Programming proficiency in Python with working fluency in PowerShell, SQL (including T-SQL), and KQL. Experience implementing identity-aware data access patterns, including row-level security and least-privilege design at the data layer. Solid understanding of HIPAA Privacy and Security Rules, PHI and PII handling, de-identification techniques, and Business Associate Agreement scoping for AI services. Demonstrated ability to write and maintain technical documentation: architecture diagrams, data flows, runbooks, and audit-readiness artifacts. Working knowledge of Responsible AI practices: bias and fairness considerations, evaluation methodology, guardrails, transparency, and human-in-the-loop design. Experience working in a Managed Service Provider (MSP), consulting, or shared-services environment serving multiple client organizations. Ability to maintain high level of confidentiality. Current driver’s license, acceptable driving record and proof of adequate insurance required. Preferred: Direct experience in a HIPAA-covered entity or business associate with hands-on responsibility for AI services governance Experience in a Managed Care Organization (MCO), payer, behavioral health, or comparable regulated healthcare environment Familiarity with the Health Sector Coordinating Council (HSCC) Health Industry AI Cyber Governance Framework, or comparable sector-specific AI governance guidance Experience leading or contributing to a Data Readiness Assessment, Master Data Management initiative, or Data Stewardship program Hands-on experience with MLOps tooling and practice (MLflow or equivalent, Docker, CI/CD for ML, drift detection and monitoring) Microsoft certifications relevant to the role (Azure AI Engineer Associate, Microsoft Certified: Power Platform Developer, Microsoft Certified: Azure Data Engineer Associate, Microsoft Applied Skills credentials, or comparable) Prior experience as a client-side counterpart to a strategic consulting engagement Familiarity with vendor evaluation discipline: ability to assess AI vendor pitches against model provenance, data residency, BAA scope, and integration feasibility Mentoring or coaching experience working with technical peers in an informal capacity

Responsibilities

Design, deploy, and operate AI solutions and retrieval-grounded agents across a client portfolio using Microsoft Copilot Studio and Azure AI Foundry. Collaborate with compliance and data teams to ensure solutions meet regulated healthcare environment standards and maintain technical documentation.