Engineering Manager - Agentic AI & SaaS

Job Title: Engineering Manager (Agentic AI & SaaS)

About The Team

The Nutanix Core Security engineering team focuses on building secure hybrid cloud platforms. This team is responsible for developing customer facing security functionalities and core platform security services. We own multiple areas that help to improve product security postures and values on AOS (NCI) and Prism Central (PC) Platforms. It has been great working closely with both internal X-functional teams and external solution partners in solving complex product security issues. We work closely with PM team to align our security features with NIST Cybersecurity Framework. Learn more about Nutanix.

What the Team Says

• We are not short of new technologies in our tech stack viz., Kubernetes, Cassandra, GoLang, Backbone JS, React, Playwright etc.
• We use AI tools for development and testing and are exploring new AI security features.
• We are not too big of a team in size, but tackling some of the biggest challenges around security in our product.
• We follow the Agile model while running bi-weekly sprints and weekly scrums.
• We are a group that is always enthusiastic to learn, adjusts plans from learnings and delivers product features with great quality.
• Last, but never the least, we love to have fun and truly strive to uphold Nutanix culture and beliefs.
  
  

Role Summary

We are seeking a hands-on, people-first Engineering Manager to lead, coach, and grow a cross-functional squad of Software Developers and QA Engineers. As a first-line manager, you will bridge the gap between technical execution and career development while driving daily engineering excellence. You will balance direct people management with active technical contribution—participating in architectural designs, personally contributing to feature development, and designing system-level AI workflows. You will guide the team from basic LLM integration to advanced, production-grade Agentic AI architectures, utilizing modern tools like the Model Context Protocol (MCP) to solve complex business problems.

Roles And Responsibilities

Team Leadership & People Management

• Empower & Grow: Lead a dedicated squad of developers and QA engineers, establishing a culture of psychological safety, high performance, and continuous technical growth.
• Direct Talent Pipeline: Own the complete talent lifecycle for your direct reports, including technical coaching, regular performance evaluations, and personalized career path planning.
• Agentic Upskilling: Upskill the team in modern AI engineering workflows, helping engineers responsibly integrate AI-assisted coding tools while leading by example in architectural planning and task decomposition.
  
  

Product, Technical & Feature Development

• Collaborative Roadmap: Partner with Support, and Customer Success to translate business goals into clear, actionable technical roadmaps.
• Hands-on Feature Delivery: Actively participate in core feature development and code contributions alongside the team, leading by example to maintain delivery velocity and high code quality.
• Agentic Architecture: Design and deploy resilient, scalable, production-grade AI applications using specialized AI agents and multi-agent orchestration patterns (e.g., LangGraph, CrewAI, or AutoGen).
• Context Engineering & Integration: Implement Model Context Protocol (MCP) servers to standardise secure, dynamic tool calling and real-time context management between your agent fleets and external enterprise data/infrastructure.
• Pragmatic Problem Solving: Dive deep into code and infrastructure to troubleshoot production incidents, manage technical debt, and stand up evaluation harnesses to prevent agent drift.
  
  

Engineering & Release Excellence

• Agile Execution: Establish software development best practices and optimize the team's sprint planning to ensure predictable, iterative, and rapid feature deployment.
• Global Coordination: Streamline release management processes, coordinating seamlessly with cross-functional and geographically distributed teams.
• Operational Oversight: Ensure timely and high-quality software releases by implementing robust monitoring, testing automation, and cloud-native CI/CD pipelines.
  
  

Skills & Qualifications

• Education: BA, BS, or MS degree in Computer Science, Engineering, or a related technical stream.
• Industry Experience: 10–12+ years of total experience in software development, with a strong foundational track record as an individual contributor.
• Leadership Experience: 2–4+ years of dedicated experience as a first-line engineering manager directly managing engineering teams.
• Hands-On Coding & Execution: Proven willingness and ability to remain hands-on, writing high-quality code and delivering product features alongside individual contributors.
• AI & Agentic Engineering: Hands-on experience developing AI applications, with deep familiarity in tool calling, planning/reasoning loops (ReAct), and configuring Model Context Protocol (MCP) environments.
• Core Tech Stack: Professional development experience in one or more core languages (e.g., Python, Golang, Java, C, C++).
• Cloud & Distributed Systems: Proven experience designing, building, and monitoring large-scale distributed microservices on public or private clouds.
• Containerization: Hands-on experience developing and deploying applications/services using Kubernetes.
• SaaS & Agile Fluency: Deep understanding of SaaS delivery models and strong working experience running high-velocity Agile/Scrum environments.
• Communication: Exceptional written and oral communication skills, with the ability to translate technical AI speak into clear business value for stakeholders.
  
  

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