Lead AI Engineer

UKG

About The Position

UKG is seeking an experienced AI Engineer to design, build, and scale AI‑driven solutions and autonomous agents that integrate with enterprise platforms such as Salesforce, ERP systems, Microsoft 365/SharePoint, and cloud services. The ideal candidate has hands‑on experience delivering real‑world AI initiatives, building agent‑based workflows using Microsoft Copilot, OpenAI/ChatGPT, Google Agentspace, or similar frameworks, and operationalizing AI within enterprise IT ecosystems. This role will work closely with engineering, architecture, product, security, and business stakeholders to translate business use cases into production‑ready AI solutions with appropriate governance, scalability, and security.

Requirements

8+ years of experience in software engineering, platform integration, or AI/ML solution development
Hands‑on experience building AI solutions using one or more of: Microsoft Copilot / Copilot Studio, OpenAI (ChatGPT, Assistants API), Google Agentspace / Vertex AI
Strong experience with AI agent concepts: Prompt engineering, Tool/function calling, RAG architectures, Agent orchestration and workflow chaining
Proficiency in one or more programming languages: Python, JavaScript/TypeScript, Java, or C#
Experience with REST APIs, event‑based integrations, and microservices
Familiarity with cloud platforms (Azure, GCP, or AWS)
Hands‑on integration experience with at least one major enterprise platform: Salesforce, ERP systems (MS Dynamics 365, etc.), Microsoft 365 / SharePoint / Teams
Strong understanding of enterprise security, authentication (OAuth, SSO), and role‑based access control
Experience working with enterprise data models and large‑scale production systems

Nice To Haves

Experience with Salesforce Apex, Flow, Platform Events, or Salesforce APIs
Experience implementing AI governance frameworks or model risk controls
Exposure to CI/CD pipelines for AI and backend services
Familiarity with LLM evaluation frameworks, test automation, or AI monitoring tools
Prior experience delivering AI solutions in regulated or large enterprise environments
Experience working with global, distributed teams

Responsibilities

Design, develop, and deploy AI agents that automate, orchestrate, or augment business workflows across enterprise platforms
Build agentic workflows using tools such as: Microsoft Copilot / Azure OpenAI, OpenAI (ChatGPT / Assistants / GPT APIs), Google Agentspace / Vertex AI, LangChain, Semantic Kernel, or similar orchestration frameworks
Implement multi‑step reasoning, tool calling, retrieval‑augmented generation (RAG), and decision logic within AI agents
Develop APIs and backend services to support AI‑driven workflows
Integrate AI solutions with enterprise systems, including: Salesforce (Sales Cloud, Service Cloud, CPQ, Revenue Cloud, custom Apex APIs), ERP systems (MS Dynamics 365, or similar), Microsoft 365 / SharePoint / Teams, Data platforms, document repositories, and internal APIs
Enable secure access to structured and unstructured enterprise data for AI use cases
Design event‑driven or workflow‑based AI integrations (e.g., case handling, opportunity lifecycle, billing events)
Contribute to enterprise AI architecture standards, patterns, and best practices
Implement prompt management, versioning, and testing strategies
Ensure AI solutions meet security, privacy, and compliance requirements (PII handling, data residency, access control)
Apply AI guardrails, validation rules, and safety controls to prevent hallucinations or misuse
Establish evaluation metrics for AI agents (accuracy, reliability, latency, business impact)
Partner with product managers, architects, platform teams, and business stakeholders to refine AI use cases
Document solution designs, integration approaches, and operational runbooks
Support PoCs, pilots, and production rollouts of AI initiatives
Provide knowledge transfer and technical guidance to internal teams