Manager Ii, Engineering – Secure Compute Platform

Confluent Confluent · Data AI · United States · Remote · Engineering

Manager II, Engineering for Confluent's Secure Compute Platform. This role focuses on building and scaling the foundational secure infrastructure for Confluent Cloud, including isolation, identity, and networking for safe execution of untrusted code. The role involves leading a team, defining a multi-year roadmap, and ensuring security, reliability, and performance. It mentions exploring AI-driven tools for team velocity and operational efficiency, and AI-driven infrastructure automation as a plus.

What you'd actually do

  1. Lead the strategic vision and multi-year roadmap for the Secure Compute Platform, aligning foundational infrastructure with company growth goals.
  2. Provide hands-on technical leadership in distributed systems, Kubernetes, and container-based runtimes to ensure world-class security and scale.
  3. Partner with Product, Security, and Cloud Infrastructure teams to define architectural standards and deliver seamless, end-to-end solutions.
  4. Cultivate a culture of technical excellence and ownership within a high-performing and inclusive engineering team. Lead, mentor, and scale a team of 6-8 engineers.
  5. Drive the exploration and adoption of AI-driven tools and workflows to accelerate team velocity and enhance operational efficiency.

Skills

Required

  • 10+ years of experience in software development
  • 3+ years in management
  • building and designing resilient systems at scale using hyperscale CSPs (AWS, Azure, GCP)
  • deep technical proficiency in Kubernetes, container internals, and lower-level systems
  • Understanding API governance frameworks and best practices
  • Ability to influence the team, peers, and upper management
  • Ability to hire, motivate engineers, coach/mentor, and manage performance
  • excellent prioritization skills

Nice to have

  • contributing to or maintaining foundational open-source projects within the cloud-native or distributed systems ecosystem (e.g., CNCF, Kubernetes)
  • build and foster a strong engineering community
  • driving the adoption of innovative platform technologies, such as AI-driven infrastructure automation

What the JD emphasized

  • secure compute layer
  • safe execution of untrusted code
  • highly regulated, multi-tenant customer base
  • world-class quality, security, and reliability
  • challenging problems in distributed systems
  • security with cost-efficiency
  • high development and management standards
  • secure compute interfaces