Dir., Software Engineering (Agentic AI)

Build and scale a high-performing team of engineers, platform architects, product managers, and AI specialists; own hiring, performance, development, and retention. Define the group's operating model, roles, rituals, and specialization areas as the organization grows. Create a culture of innovation, technical excellence, psychological safety, customer obsession, and continuous learning. Strategy & Business Impact Define OKRs and success metrics for adoption, engineering velocity, quality, cost efficiency, and developer satisfaction; translate platform capabilities into business value. Partner with engineering and product leaders across divisions to align on standards, gather requirements, and drive transformational change at scale. Establish the architecture for organization-wide agentic AI capabilities across Google ADK and complementary platforms, including orchestration, extensibility, and integration patterns. Guide innovation in multi-agent systems, tool ecosystems, human-in-the-loop workflows, and production readiness for safety, cost, latency, and reliability. Define agent safety, governance, and responsible AI controls in partnership with security, legal, and compliance teams. Execution & Operational Excellence Build platform instrumentation and observability to measure agent performance, developer adoption, quality impact, reliability, and ROI. Set standards for service health, SLAs, incident response, reliability, uptime, and cost management for agentic systems. Communicate progress, trade-offs, and strategic decisions clearly to engineering VPs, product leaders, and executive stakeholders. Stay current with agentic AI research, evaluate emerging technologies, and foster a culture of experimentation and learning. Build strategic relationships with technology partners such as Google, Anthropic, and platform vendors to accelerate innovation. Drive internal knowledge sharing through documentation, training, engineering blogs, lunch-and-learns, and communities of practice. Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent experience. 12+ years of professional software development experience, including 5+ years in engineering leadership roles managing managers or teams of 15+ engineers. 3+ years of hands-on experience building production agentic AI systems, LLM-powered applications, or AI/ML platforms at scale. Proven ability to build, scale, and retain high-performing engineering teams. Deep technical expertise in agentic AI platforms such as Google ADK, Anthropic Claude SDK, LangChain, or LangGraph, with the ability to guide architecture and technical direction. Strong understanding of prompt engineering, agent design patterns, multi-agent orchestration, and production AI system challenges including safety, cost, latency, and reliability. Demonstrated success driving large-scale technical transformation, organizational change, and adoption programs across multiple teams or organizations. Experience defining product strategy, building roadmaps, and delivering results in complex, ambiguous environments. Experience with cloud platforms, modern DevOps practices, and enterprise-scale software delivery. Exceptional communication, influence, stakeholder management, and business acumen, with the ability to connect technical investments to measurable business outcomes.