Engineering Team Lead, Automation, Performance & Scale

Mirantis

. Lead, hire, and grow the k0rdent AI automation and performance engineering team .

Posted 11/9/2026full-timeRemote • Texas • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading performance engineering and test automation teams, with a strong focus on defining acceptance criteria, driving testing methodologies, and ensuring measurable performance metrics. Proficient in hands-on coding, designing frameworks, and integrating automated testing within CI/CD pipelines.

Highest-signal resume keywords

Performance EngineeringTest Automation EngineeringKubernetes ExpertiseCI/CD Pipeline ManagementPython Programming

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Applicant Tracking System Keywords

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Hard Skills

Test AutomationPerformance TestingAPI TestingLoad TestingPython ProgrammingShell ScriptingKubernetesCI/CDInfrastructure as CodeFailure Injection

Soft Skills

LeadershipCommunicationCollaboration

Tools & Technologies

PytestK6JMeterDockerTerraformPrometheusGrafanaGitOpsAnsibleCluster API

Industry Keywords

AI AutomationPerformance MetricsTest MethodologiesChaos EngineeringDistributed SystemsMulti-Region TopologiesObservabilityOpenTelemetryCNCF ContributionsGPU Workload Scheduling

Tech Stack

Tools & technologies

AnsibleCloudDistributed SystemsDockerFluxGrafanaJMeterKubernetesLinuxPrometheusPythonShell ScriptingTerraformUnixGo

About the role

Key responsibilities & impact

Lead, hire, and grow the k0rdent AI automation and performance engineering team
Set direction and priorities, run planning, coach engineers, and own delivery of team commitments
Define k0rdent AI release acceptance criteria and exit gates
Coordinate verification across component teams and drive evidence-based go/no-go decisions for releases, upgrade paths, and hotfixes
Drive shift-left testing, test pyramids, contract and integration testing, definition of done, CI quality gates, and test-code review standards
Participate in roadmap planning and estimation, assessing testability and non-functional risk
Ensure performance, scale, and reliability requirements are explicit and measurable
Establish and report quality and performance metrics to engineering and product leadership
Convert field issues and customer scenarios into automated coverage with product management, development, SRE, and support teams
Design, build, and evolve API, end-to-end, upgrade, and multi-cluster test automation frameworks
Own performance and scale testing for control-plane scalability, GPU workload scheduling and utilization, and AI inference/serving throughput and latency
Conduct soak, endurance, resilience, failure-injection, upgrade/rollback, backup/restore, disaster-recovery, security, and tenant-isolation testing
Build reproducible on-demand test environments and infrastructure as code across local, multi-cluster, multi-region, and bare-metal GPU topologies
Integrate automated suites and performance regression checks into CI/CD pipelines
Automate test-result collection, storage, trend analysis, and triage; build observability and dashboards
Debug complex cross-stack failures, trace issues into service code, and partner with component teams on root-cause fixes

Requirements

What you’ll need

5+ years in software engineering, test automation, performance engineering, or SRE/platform engineering
2+ years leading engineers
Ability to remain hands-on while leading, including designing frameworks, writing production-quality code, and reviewing work
Strong knowledge of testing methodologies and techniques
Strong test automation engineering with Python test frameworks such as pytest or equivalent
Experience with API and end-to-end testing, test data and environment management, and maintaining fast, non-flaky suites
Hands-on experience designing and executing performance, load, and scale tests for distributed systems or API platforms
Experience with tools such as k6, Locust, JMeter, kube-burner, or ClusterLoader2
Experience with profiling, capacity analysis, and translating results into actionable engineering findings
Experience with failure injection, chaos engineering, soak testing, and upgrade/rollback verification
Strong Kubernetes experience, including workloads, networking, storage, RBAC, CRDs and operators, Cluster API, Helm, and cluster upgrades
Strong coding ability in Python and shell scripting
Enough Go to read service code, write tooling or tests, trace failures, and file precise bugs
Experience owning or defining release acceptance and go/no-go processes for complex infrastructure products
Strong CI/CD experience with pipelines as code, quality gates, and versioned release workflows
Git-based workflow fluency
Experience building environments as code on Linux/UNIX using Docker, virtualization, Terraform or Ansible, and GitOps tools such as Argo CD or Flux
Experience with Prometheus, Grafana, and centralized logging
Experience contributing to roadmap planning, estimation, and prioritization
Excellent communication with geographically distributed international teams
Strong spoken and written English
Nice-to-have: k0s or k0rdent ecosystem experience; GPU infrastructure on Kubernetes; AI/ML workload benchmarking; public cloud providers; bare-metal provisioning; multi-region topologies; stateful supporting stacks; OpenTelemetry; security and policy testing; CNCF open-source contributions

Benefits

Comp & perks

Competitive compensation package with strong benefits plan
Work with an established leader in the cloud infrastructure industry
Work with passionate, talented and engaging colleagues
Help Fortune 500 and Global 2000 customers implement next-generation cloud technologies
Participate in cutting-edge, open-source innovation
High-energy environment valuing openness, collaboration, risk-taking, and continuous growth