Sr. Staff Software Engineer- Eng

Technical Strategy and Direction: Own the technical strategy and vision for agentic AI across the Agentic Acceleration Group and its consuming value streams, ensuring alignment with business goals and industry best practices. Set the 12-24 month direction for how UKG builds agents: platform selection, orchestration standards, and evaluation methodology. Make build-vs-buy and platform-bet calls, and defend them to senior engineering and product leadership. Drive multi-team initiatives where no roadmap exists yet. Frame ambiguous business problems into agentic technical charters, partition them across teams, and keep independently-owned workstreams converging. Operate with no guidance on scope, escalating only on org-level tradeoffs. Communicate complex agent architectures to non-technical stakeholders, anticipate potential objections, and influence others to adopt a point of view. Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 10+ years of professional software development experience, with 3+ years building agentic AI systems or LLM-powered applications in production at scale. Proven track record of setting technical direction across multiple teams, not just leading one. Experience taking an agentic system from prototype to production at enterprise scale: multi-tenant, regulated data, SLA-backed. Hands-on experience building production agents using platforms such as Google ADK, Anthropic Claude SDK, LangChain, LangGraph, or similar agentic frameworks. Experience designing and implementing multi-agent systems, agent orchestration patterns, and tool-use architectures. Strong understanding of prompt engineering, context engineering, and agent design patterns (ReAct, Chain-of-Thought, tool use, multi-agent collaboration). Experience integrating agents with enterprise systems through APIs, tools, and protocols (REST APIs, MCP, function calling). Deep expertise in one or more programming languages such as Python, Java, C#, JavaScript, or TypeScript. Extensive experience with software architecture and design patterns, including the ability to design and implement scalable, reliable agentic systems in a DevOps model. Proven track record of leading and delivering large-scale, complex software projects including agentic AI initiatives. Strong understanding of cloud technologies and DevOps principles, including GCP (Vertex AI, Google ADK), Azure (Azure OpenAI), or AWS (Bedrock), and version control systems like GitHub. Excellent problem-solving skills and attention to detail, with a commitment to delivering high-quality agent-powered solutions. Excellent communication and leadership skills, with a demonstrated ability to influence and drive agentic AI technical decisions across the organization and translate agent capabilities to non-technical stakeholders. Master's degree or PhD in Computer Science, Engineering, or a related technical field. Demonstrated ability to define evaluation and safety standards that other teams adopted. Experience owning inference cost and model-selection strategy at scale. Proficiency in building telemetry and observability for agentic systems (execution tracing, decision logging, cost monitoring, success rate tracking). Experience building or contributing to MCP servers and reusable tool layers consumed by other teams. Understanding of RAG patterns, context engineering, and agentic workflow design. Experience shaping vendor or platform partner roadmaps through early-access or design-partner programs. Familiarity with CI/CD pipelines and automation tools. Demonstrated commitment to diversity and inclusion initiatives. Familiarity with developing accessible technologies.