[Remote] Senior Manager, Software Engineering - Infrastructure

Note: The job is a remote job and is open to candidates in USA. ClickUp is building an AI-native workspace that unifies tasks, docs, chat, calendar, and enterprise search. The Senior Manager will lead infrastructure and product engineering initiatives, set cloud strategy, scale a secure multi-shard and multi-region platform, drive AI-powered tooling adoption, and manage a distributed senior engineering team.

Responsibilities

• Cost Efficiency: Deliver measurable annual infrastructure savings by executing the migration of data workloads to EKS and self-hosting key services
• Ingress Convergence: Deprecate legacy frontend ALBs and consolidate to a single EKS-managed ALB per shard, unblocking faster deployments across the org
• Coverage & Bench Depth: Eliminate single points of ownership across Networking, OpenSearch, and Terraform through cross-training and targeted hiring
• Stakeholder Alignment: Stand up a recurring alignment cadence with Product, AI, Enterprise, and Security so infra planning is driven by demand, not ad-hoc interrupts
• Automation: Ship automated shard buildout via Backstage to remove manual toil from enterprise scaling
• Reliability: Cut P0/P1 incidents attributed to Cloud Platform (DNS, ALB misconfiguration, EKS) through hardened ingress patterns and Terraform-policy guardrails. Own incident response and RCA follow-through for the team
• Roadmap Ownership: Own and deliver against the team's roadmap for Agent enablement, centralized IaC, and deployment rollout acceleration, and contribute to the broader Cloud Platform strategy tied to AI and Enterprise revenue goals
• Technical Leadership: Architect and contribute code to key initiatives (EKS migration, ALB consolidation, Backstage shard automation), and lead design reviews with senior engineers
• People Leadership: Lead, grow, and retain a senior-heavy team distributed across the US, Canada, and Europe, spanning FTEs and contractors, with a focus on career development, cross-training, and bench depth
• Vendor Management: Partner with Finance and leadership on AWS spend visibility and savings targets, manage contractor performance and budget, and keep a savings-pipeline mindset baked into planning

Skills

• Experience: 9+ years in infrastructure/platform engineering, including 5+ years in engineering management leading distributed teams of senior engineers while remaining hands-on
• Deep AWS infrastructure mastery: EKS, networking (VPC/TGW/DNS), and Terraform at scale, with strong architectural judgment; able to review designs and guide senior engineers' technical decisions
• Hands-on technical leadership: Actively architects, writes code, and develops systems alongside the team. You are a working engineer as well as a manager
• Strategic roadmap ownership: Experience translating cloud priorities into 3–9 month team roadmaps tied to business outcomes across enterprise, AI, and cost, and delivering against them
• Cross-team influence: Builds genuine partnerships across Product, Security, SRE, and DB orgs, driving shared ownership across traditional infra/product boundaries
• Application-level curiosity: Genuinely understands what the product does, not just the infrastructure underneath, and extends ownership past traditional platform boundaries
• People leadership: Proven experience managing, growing, and retaining senior, geographically distributed teams across FTE/contractor blends; builds bench depth and contributes to succession planning
• Hiring: Experience running structured hiring loops and closing senior engineers, including into specialized gaps (networking, search, IaC)
• Operational rigor: Strong on-call instincts, incident ownership, and RCA follow-through
• Security-first instincts: This team touches blast radius (auth enforcement, network isolation, shard boundaries). A verify-first, never-assume mindset is non-negotiable
• AI & automation mindset: Uses AI tools daily in your own engineering work, with demonstrated appetite for DevSecOps agents, AI-assisted IaC migrations, and skills-based automation — a core part of the near-term roadmap
• Education: BS/MS in CS, Engineering, or equivalent
• AI/ML infrastructure experience (strong plus): Scaling workloads like GPU orchestration, model-serving infrastructure, or cost-optimized compute for inference

Company Overview

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