Senior Platform Engineer

As a Senior Platform Engineer, you will build and operate the shared platform that application teams use to deploy and run services on Azure Kubernetes Service. You will work with infrastructure defined through Terraform and delivered using GitHub Actions and GitOps practices.

This position provides broad technical ownership across continuous and progressive delivery, multi-region resiliency, disaster recovery, policy and compliance automation, and AI-assisted platform tooling. You will own platform capabilities from design and development through implementation and measurement, while establishing standards and reusable solutions that support engineering teams across the organization.

Position Responsibilities:

• Build and operate continuous and progressive delivery capabilities for services running on Azure Kubernetes Service.
• This includes GitHub Actions pipelines, Terraform modules, GitOps reconciliation, and canary and blue/green deployments through a service mesh, supported by versioning, phased rollouts, and tested rollback procedures.
• Own and continuously improve shared CI/CD workflows and reusable Terraform module catalogues that application teams can confidently adopt.
• Transform recurring platform requests into self-service capabilities and automated guardrails, while creating reference implementations, standards, and documentation for other engineers.
• Design and test highly available, resilient solutions across multiple Azure regions.
• Automate regional failover across infrastructure, traffic-routing components, and dependent Azure services, and conduct controlled chaos experiments to validate recovery capabilities.
• Integrate observability, service-level indicators, service-level objectives, release gating, and rollback capabilities into the delivery process so that release outcomes are evaluated using service behavior.
• Establish secure and compliant delivery paths by default through Azure Policy, in-cluster admission controls, and workload identity.
• Design and deliver AI-assisted platform tooling using agent-based solutions and the Model Context Protocol for onboarding, configuration validation, access auditing, drift detection, and incident triage.
• Incorporate appropriate approval gates, checkpointing, and auditability into AI-assisted platform solutions.

Required Qualifications:

• 8+ years of experience in software, platform, or infrastructure engineering, including ownership of at least one end-to-end platform capability used by other teams.
• 8+ years of experience working with Azure in an enterprise environment, including Entra ID, workload identity, networking, governance, Azure Policy, Key Vault, and managed data and messaging services.
• 5+ years of experience operating production Kubernetes environments across multiple clusters and regions, including experience with a service mesh such as Istio or an equivalent technology.
• 5+ years of experience supporting progressive delivery through canary or blue/green deployment approaches.
• 4+ years of experience with Terraform and CI/CD, including developing reusable modules used by other teams.
• 4+ years of experience developing GitHub Actions reusable workflows that incorporate approval gating and OpenID Connect federation with Azure.
• 2+ years of production experience with GitOps technologies such as Flux CD or Argo CD.
• Production experience working with Python, Bash, YAML, and containers.
• 2+ years of hands-on experience with observability and policy as code, including an application performance monitoring platform such as New Relic or Datadog, SLI and SLO development, and admission-control policies enforced within Kubernetes clusters.
• Current, hands-on experience building solutions using large language models, including agent frameworks, tool calling, or the Model Context Protocol, and applying these technologies to infrastructure or operational challenges.
• Experience delivering technology solutions in a regulated enterprise environment with formal change-management, control, and audit requirements.

Preferred Qualifications:

• Experience with chaos engineering and formal disaster-recovery testing using Chaos Mesh, Azure Chaos Studio, or an equivalent technology.
• Experience building Model Context Protocol servers or agentic workflows that incorporate state management, checkpointing, and human approval gates using Azure OpenAI or Azure AI Foundry.
• Experience operating a service mesh at scale, including traffic management, distributed tracing, and mesh observability.
• Experience with API management platforms and the automated promotion of API configurations between environments.

When you join our team:

• We’ll empower you to learn and grow the career yo