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UKG is seeking a Sr. Staff Software Engineer to set the technical direction for agentic AI and scale it across the organization.
You will define how UKG builds agents on Google’s Agent Development Kit (ADK) and other platforms, own the reference architecture, and translate ambiguous business problems into technical charters for multiple teams. You will operate ahead of the roadmap, defend platform bets to senior leadership, and drive design, development, testing, deployment, and maintenance of
At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That’s what we do.
We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you.
We are seeking a Sr. Staff Software Engineer to set the technical direction for agentic AI at UKG and scale it across the organization. You will define how UKG builds agents on Google’s Agent Development Kit (ADK) and other enterprise agentic platforms, own the reference architecture that consuming teams build on, and turn ambiguous business problems into technical charters that multiple teams execute against. You will operate ahead of the current roadmap, make platform bets and defend them to senior engineering and product leadership, and raise the ceiling of what the organization is capable of building. As a Sr. Staff Software Engineer, you will be responsible for the design, development, testing, deployment, and maintenance of highly complex agentic systems.
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. Play a pivotal role in the R.I.D.E. (Recommend, Inform, Decide, Execute) framework.
Own the reference architecture for agentic systems at UKG: multi-agent coordination patterns, task delegation workflows, agent communication protocols, and the shared tool and MCP layers reused across teams. Set the patterns other teams build on, not just the ones your team uses, ensuring high standards of performance, scalability, and reliability. Partner with architects on mid-level and high-level design, and on enterprise alignment across value streams.
Design, build, and deploy production-grade AI agents using Google ADK and other agentic platforms (LangGraph, N8N, Temporal, etc.). Write clean, maintainable, and efficient code for agent workflows, tool integrations, and multi-agent orchestration. Stay hands-on with code, remaining credible in design reviews and able to unblock the hardest problems yourself. Build agents that integrate with enterprise systems through tools, APIs, and Model Context Protocol (MCP) servers. Design and implement custom tools, skills, and plugins that extend agent capabilities across UKG’s HCM platform, built for reuse by other teams rather than for a single use case.
Ensure the health and quality of agent-powered services, proactively identifying and addressing issues. Utilize service health indicators, agent performance metrics (task success rates, latency, cost), and telemetry for action. Conduct thorough root cause analysis for agent failures and implement measures to prevent future recurrences. Oversee agent deployment, monitoring, and lifecycle management. Establish best practices for agent versioning, cost monitoring, performance optimization, and iterative improvement. Build observability into agent workflows including execution tracing, decision logging, and failure analysis. Own the