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Nutanix is seeking a hands-on Engineering Manager to lead a cross-functional squad of software developers and QA engineers within the Core Security engineering team. This role bridges technical execution and people leadership, requiring active participation in architectural design, feature development, and system-level AI workflows alongside direct reports.
You will empower and grow a dedicated team while establishing a culture of psychological safety and high performance. Responsibilities include owning the complete talent lifecycle—technical coaching, performance evaluations, and personalized career path planning. A key focus is upskilling the team in modern AI engineering workflows, helping engineers responsibly integrate AI-assisted coding tools while leading by example in architectural planning.
On the technical side, you will partner with product, support, and customer success teams to translate business goals into actionable technical roadmaps. You'll actively participate in core feature development and code contributions, designing and deploying resilient, production-grade AI applications using specialized AI agents and multi-agent orchestration patterns (LangGraph, CrewAI, AutoGen). You'll implement Model Context Protocol (MCP) servers to standardize secure, dynamic tool calling and real-time context management between agent fleets and external enterprise data.
You will establish software development best practices, optimize sprint planning for predictable and rapid feature deployment, and streamline release management processes across geographically distributed teams. Responsibilities include troubleshooting production incidents, managing technical debt, and implementing robust monitoring, testing automation, and cloud-native CI/CD pipelines.
Required qualifications include 10–12+ years of software development experience with a strong individual contributor track record, plus 2–4+ years as a first-line engineering manager. You must have hands-on experience developing AI applications with deep familiarity in tool calling, planning/reasoning loops (ReAct), and MCP configuration. Professional development experience in Python, Golang, Java, C, or C++ is essential, along with proven experience designing large-scale distributed microservices on public or private clouds. Kubernetes containerization experience and deep understanding of SaaS delivery models and Agile/Scrum environments are required. Exceptional communication skills to translate technical concepts into clear business value are critical.
