DevOps Team Lead
The DevOps Team Lead owns the delivery, reliability, and day-to-day operation of our AWS cloud platform, an extensive multi-account cloud environment managed as code and expanding toward globally distributed, multi-region workloads.
This is a highly hands-on technical leadership role. You'll be one of the strongest technical contributors on the team while also helping shape and prioritize the work. You'll translate product and engineering needs into infrastructure requirements, guide the team's delivery, and ensure what we build is automated, secure, documented, cost-conscious, and operationally reliable.
The role is approximately 60% hands-on engineering and 40% technical leadership, including requirements, planning, review, coordination, and coaching.
What You'll Do
Design, build, review, and operate our Infrastructure-as-Code estate across a multi-account AWS environment, including reusable modules, environment configurations, state management, and account provisioning.
Own and improve CI/CD pipelines for infrastructure changes, including automated validation, security and compliance controls, and keyless cloud authentication.
Build and maintain the core AWS services supporting our products, including networking, containers, databases, storage, messaging, systems management, backup, monitoring, and cost controls.
Establish and reinforce practical engineering standards around IaC, IAM, resource tagging, state management, versioning, security, documentation, and operational readiness.
Translate ambiguous requests from product, engineering, security, and data teams into clear requirements, milestones, estimates, dependencies, and acceptance criteria.
Own and refine the DevOps backlog and facilitate the team's Scrum cadence, including planning, stand-ups, refinement, reviews, and retrospectives.
Strengthen platform reliability through observability, SLOs, actionable alerting, runbooks, disaster recovery, backup and restore practices, and continuous reduction of operational toil.
Participate in a rotating night and weekend on-call schedule and provide technical leadership during platform incidents, including incident coordination and post-incident follow-through. Rotation frequency will depend on team size and coverage needs but is shared equitably across the team.
Partner with security to embed identity, least-privilege access, network segmentation, encryption, secrets management, audit logging, and compliance requirements into the platform.
Lead cloud cost visibility and optimization, including tagging, right-sizing, commitment planning, anomaly response, and the cost implications of multi-region architecture.
Help evolve the platform toward globally distributed workloads, including regional rollout, data residency and replication, latency-aware routing, cross-region failover, and associated operational tradeoffs.
Use AI tools effectively in engineering workflows and help design and operate the cloud infrastructure needed to support emerging AI capabilities.
Set technical direction in partnership with architecture and coach engineers through code review, pairing, design discussions, documentation, and shared platform ownership.
What You'll Bring
Extensive experience in software engineering, infrastructure, or DevOps, with demonstrated experience operating at a senior or technical lead level in complex cloud environments.
Expert-level, current hands-on experience with Terraform or equivalent Infrastructure as Code, including managing large-scale cloud environments through IaC.
Experience with IaC at scale, including reusable module design and versioning, state architecture, safe refactoring, upgrades, drift detection and remediation, and bringing legacy infrastructure under IaC management.
Deep hands-on AWS experience across compute, storage, networking, IAM, and security, ideally within a multi-account AWS Organization.
Proven ownership of infrastructure CI/CD pipelines, including automated policy, validation, and security controls.
Experience designing and operating containerized or distributed production workloads with appropriate networking, security, and observability.
Scripting proficiency and a track record of automating operational work.
Demonstrated ownership of production operations, including on-call, incident response, runbook development, and the ability to independently troubleshoot and resolve platform issues.
Experience leading Agile/Scrum practices, including backlog ownership, refinement, estimation, planning, and stakeholder negotiation.
Strong ability to turn ambiguous needs into thorough, actionable technical plans that account for requirements, dependencies, risks, milestones, and estimates.
Strong understanding of cloud security, compliance, and risk management, including least privilege, zero trust, encryption, and appropriate exception management.
Excellent written communication, documentation, and stakeholder engagement skills.
A self-directed, collaborative approach with a focus on improving systems rather than repeatedly working around problems.
Willingness and ability to participate in a rotating night and weekend on-call schedule and independently manage production incidents while on call.
Preferred Experience
Microsoft Azure experience, particularly Azure Cloud Adoption Framework concepts, landing zones, governance, policy, cost management, and IaC tooling.
Experience operating globally distributed or multi-region applications, including data replication, global routing, failover, data residency, and regional compliance considerations.
Experience with monorepo IaC environments, policy-as-code, IaC security tooling, or automated code-quality platforms.
FinOps experience, including tagging-based cost allocation, commitment planning, anomaly detection, and multi-region cost analysis.
SRE practices, including SLOs, error budgets, observability, and structured incident management.
Experience supporting analytics, data engineering, database, or integration workloads as a platform provider.
AWS certification such as Solutions Architect Professional, DevOps Engineer Professional, or Security Specialty.
Experience with hybrid connectivity to on-premises environments or improving software development lifecycle practices.
Experience provisioning or operating infrastructure for AI/ML platforms, including model serving, vector stores, accelerated compute, or supporting data pipelines.
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