Sr. Staff Software Engineer- Eng

UKG•Sunrise, FL

7d•$145,600 - $209,300

About The Position

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.

Requirements

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.

Nice To Haves

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.
Knowledge of agile development methodologies.
Experience in a complex, matrixed organization.
Demonstrated commitment to diversity and inclusion initiatives.
Familiarity with developing accessible technologies.

Responsibilities

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 economics of agentic systems. Set token and inference budgets, define model-tier routing policy, and measure agent ROI against the manual workflows they replace. Make the case for spend to engineering leadership and finance.
Define the organization’s guardrail standards for autonomous action on customer payroll and HR data: permission boundaries, human-in-the-loop thresholds, audit trails, and blast-radius limits.
Partner with Security, Legal, and Privacy to make those standards enforceable, and gate production launches against them.
Ensure AI-enabled features are introduced safely, transparently, and compliantly.
Define the agent evaluation bar for the organization: what “good” means for task success rate, cost per task, and safety, and gate production launches against it.
Advocate for and implement best quality practices for agentic systems, hold a high bar for engineering excellence, and guide teams in maintaining service quality through comprehensive testing (including agent evaluation, prompt testing, and tool validation).
Build testable agents and agentic systems, define tests including agent evaluation and tool validation, and automate tests using appropriate frameworks.
Implement agent-specific testing strategies including prompt validation, multi-step workflow testing, tool invocation testing, and adversarial scenario testing.
Grow the organization’s agentic bench. Mentor Senior and Staff engineers, sponsor them into technical leadership, and raise the ceiling of what the organization can build.
Turn hard-won lessons into reusable patterns, internal guidance, and design reviews that other teams depend on.
Stay current with emering agentic AI technologies and platforms, advocating for their adoption where appropriate to drive innovation and productivity enhancement across the organization.
Represent UKG with platform partners including Google (Vertex AI, ADK) and Anthropic to shape their roadmap and secure early access, and make org-wide adoption calls on emerging frameworks.