Full-Time/Direct Placement - Senior AI Application Developer - Waukesha, WI

SGA is searching for a Senior AI Application Developer for an opportunity with one of our premier clients in Waukesha, WI.

About the role

This is a hands-on AI engineering role focused on designing, building, and operationalizing production-grade AI applications across manufacturing, supply chain, quality, finance, and enterprise operations. The engineer will expand and harden an existing pre-production AI platform, developing intelligent retrieval, AI agents, enterprise integrations, and governance capabilities.

Responsibilities

• Design and develop LLM-powered applications, including AI agents, RAG/search, automated reporting, and decision-support solutions.
• Build agentic workflows capable of multi-step reasoning, tool/function calling, and enterprise workflow execution.
• Develop RAG pipelines connecting ERP data, documents, technical manuals, maintenance records, and knowledge bases.
• Integrate AI solutions with ERP, data warehouses, production systems, and enterprise applications through secure APIs and connectors.
• Develop hybrid solutions combining deterministic data processing with AI-generated analysis, anomaly detection, and business insights.
• Implement AI governance and safety controls including authentication, authorization, output validation, data protection, hallucination mitigation, auditability, and human approval workflows.
• Deploy applications into production with logging, monitoring, performance and cost tracking, evaluation, and regression testing.
• Apply LLMOps practices, including prompt management, model evaluation, token optimization, and performance monitoring.
• Partner with security, compliance, legal, data, infrastructure, and business teams to ensure responsible AI adoption.
• Mentor existing developers and help establish scalable AI engineering practices and standards.

Requirements

• 5+ years of professional software development experience building production applications.
• Hands-on experience developing and deploying LLM/Generative AI applications.
• Experience building AI agents and multi-step workflows using tools such as LangGraph, LangChain, Semantic Kernel, Microsoft Agent Framework, or equivalent.
• Strong development skills in at least two of Python, C#/.NET, and TypeScript, with the ability to work across multiple application layers.
• Strong SQL skills, including relational database design, stored procedures, query optimization, and enterprise RDBMS platforms such as SQL Server.
• Experience with RAG, intelligent search, or retrieval-based AI applications.
• Experience integrating enterprise applications through REST APIs and modern authentication including OAuth2/OIDC, JWT, Windows/Active Directory integration.
• Working knowledge of Azure or AWS, including deployment, security, identity, and monitoring.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience.

Preferred Qualifications

• Experience with Model Context Protocol (MCP) servers/clients and enterprise tool integrations.
• Experience with vector databases and RAG technologies such as Azure AI Search, pgvector, Pinecone, Weaviate, or FAISS.
• Experience with AI evaluation/observability tools such as RAGAS, DeepEval, LangSmith, or comparable frameworks.
• Experience with LLMOps, prompt versioning, cost/token monitoring, and automated AI regression testing.
• Experience building real-time AI interfaces using SignalR, WebSockets, SSE, AG-UI, CopilotKit, React/Next.js, or Blazor.
• Experience with Windows Server, IIS, PowerShell, and CI/CD pipelines.
• Experience working within regulated enterprise environments with formal security, compliance, change-management, and audit requirements.
• Manufacturing, supply chain, industrial operations, or plant-floor experience.
• Experience with JD Edwards EnterpriseOne, SAP, or enterprise data platforms such as Azure Fabric/Synapse, Snowflake, Databricks, or Redshift.
• Experience mentoring developers and leading adoption of emerging AI technologies.
• Familiarity with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or Aider.

Ideal Candidate

The ideal candidate is a hands-on software engineer who has moved beyond AI experimentation into production AI engineering. They should be comfortable working across Python/.NET/TypeScript, enterprise data, APIs, LLMs, agents, RAG, and cloud/on-prem infrastructure while understanding the security, governance, reliability, and scalability requirements of a large enterprise.