Principal Software Engineer - Environments Engineering

Role overview

Platform responsibilities

• Architect composable virtual environments that reuse unchanged services and instantiate only components under test.
• Design traffic routing, service discovery, and isolation to prevent cross-session contamination.
• Build dependency-graph intelligence for live services, reused baselines, and virtualized or stubbed dependencies.
• Deliver self-service provisioning through CLI, APIs, and developer portal integration.
• Define synthetic and masked test data, snapshots/restores, schema versioning, and repeatable datasets across heterogeneous stores.
• Implement environment lifecycle controls, quotas, cost governance, automatic teardown, chargeback, and FinOps reporting.
• Integrate provisioning, testing, reporting, and teardown into CI/CD pipelines.
• Support reliable operations across on-premises Kubernetes, EKS, VMs, and managed cloud services.
• Establish SLOs, observability, runbooks, and product metrics for reliability and developer experience.

AI-enabled engineering

• Architect and govern agentic AI-enabled engineering workflows to improve delivery speed, code quality, and operational outcomes.
• Set guardrails for validation, security, resiliency, and reuse; apply authorized SDLC tools and AI-assisted development capabilities.

Required qualifications

• 15+ years of software engineering experience, with significant experience in developer platforms, environment-as-a-service, or large-scale infrastructure orchestration.
• Experience designing composable/virtual environment architectures, dependency resolution, and traffic isolation.
• Deep routing and service-mesh expertise; production Kubernetes across on-premises and cloud/EKS environments.
• Proficiency in Go, Rust, or Java and infrastructure as code with Terraform, Ansible, or equivalent.
• Automated provisioning of stateful infrastructure and experience with heterogeneous data stores.
• CI/CD design and extension across Jenkins, Spinnaker, GitHub Actions, or Argo CD.
• Platform-as-a-product thinking, and demonstrated adoption at scale through self-service, enablement, and engineering leadership partnership.
• Experience leading agentic AI development practices with human-in-the-loop validation, traceability, secure data handling, and responsible-AI governance.

Preferred qualifications

• Namespace-per-PR isolation, GitOps environment-as-code, scalable test data, or Backstage/developer portal integration.
• AI/ML for infrastructure optimization, enterprise open-source evaluation, hybrid connectivity, or regulated financial-services operations.

Compensation

• The employer describes competitive total rewards and benefits; eligible roles may receive incentive compensation. No specific salary cadence or amount is stated in the description.

About the team