Staff Software Engineer (Agentic AI)

Staff Software Engineer - Agentic Acceleration Group

Responsibilities

• Agent Development: Design, build, and deploy production-grade AI agents using Google ADK and other agentic platforms (Anthropic Claude SDK, LangGraph, etc.). Write clean, maintainable, and efficient code for agent workflows, tool integrations, and multi-agent orchestration. • Platform Integration: 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. • Technical Strategy: Drive the technical strategy and vision for agentic AI initiatives and major projects, ensuring alignment with business goals and industry best practices. Communicate complex agent architectures to non-technical stakeholders, anticipate potential objections, and influence others to adopt a point of view. • Leadership: Lead cross-functional teams to design, develop, and deliver high-impact agent-powered projects on time and within budget. Coordinate activities and tasks of other team members, working independently and needing guidance only in the most complex situations. • Architectural Excellence: Architect, design, and develop complex agentic systems and applications built on Google ADK and similar platforms, ensuring high standards of performance, scalability, and reliability. Design multi-agent coordination patterns, task delegation workflows, and agent communication protocols. Collaborate with architects on mid-level and high-level design. • Service Health and Quality: 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. • Agent Operations: Oversee agent deployment, monitoring, and lifecycle management. Implement 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. • Engineering Excellence Practices: Advocate for and implement best quality practices for agentic systems, hold a high bar for engineering excellence, and guide the team in maintaining service quality through comprehensive testing (including agent evaluation, prompt testing, tool validation). • Testing: Build testable agents and agentic systems, define tests including agent evaluation and tool validation, automate tests using appropriate frameworks. Implement agent-specific testing strategies including prompt validation, multi-step workflow testing, tool invocation testing, and adversarial scenario testing. • Mentorship: Provide technical mentorship and guidance on agent development, fostering a culture of learning and continuous improvement. Mentor junior engineers on building production-grade agents, designing tool integrations, and implementing agent safety practices. • Innovation: Stay current with emerging agentic AI technologies and platforms (Google ADK, Anthropic Claude SDK, LangGraph, AutoGen, Crew AI), advocating for their adoption where appropriate to drive innovation and productivity enhancement within the team. Explore new agent capabilities, tool integrations, and orchestration patterns.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. • 7+ years of professional software development experience, with 2+ years building agentic AI systems or LLM-powered applications in production. • Deep expertise in one or more programming languages such as Python, Java, C#, JavaScript, or TypeScript. • 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). • 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. • Proficiency with cloud technologies like GCP (Vertex AI, Google ADK), Azure (Azure OpenAI), AWS (Bedrock), and version control systems like GitHub. • Strong problem-solving skills and attention to detail, with a commitment to delivering high-quality agent-powered solutions. • Proficiency in building telemetry and observability for agentic systems (execution tracing, decision logging, cost monitoring, success rate tracking). • Strong leadership, communication, and interpersonal skills, with the ability to influence and drive agentic AI technical decisions across the organization and translate agent capabilities to non-technical stakeholders.

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