Your Future Evolves Here

Role Overview 

As a Senior Platform Engineer in Evolent's Platform Engineering & Operations (PEO) organization, you will build, automate, and improve the cloud and infrastructure platforms that Evolent's applications run on. You will work inside one PEO function and be measured on how much manual effort you remove from the way Evolent delivers and operates technology. 

Why This Role Matters

Evolent is transforming how it builds and operates infrastructure under a refreshed Platform Engineering & Operations operating model, grounded in four principles: Architecture First, Automation by Default, Reliability is a Shared Responsibility and Golden Paths Over Custom Solutions. You will turn approved designs into provisioned, automated, and documented platforms, and you will do it transparently, through formal handoffs, Office Hours reviews, and documentation your peers can actually rely on.

Agentic AI: Platform Engineering is moving toward agentic AI as a standard part of how the organization works. As agentic AI transforms the way we work, we expect our engineers to be at the forefront of that change, designing and building intelligent solutions rather than simply consuming them. This builder mentality is a core attribute we assess from the first conversation.

What You'll Be Doing

• Provision and change infrastructure exclusively as code, so that every environment is reproducible, reviewable, and free of manual drift.
• Reverse engineer the applications and infrastructure you inherit: trace dependencies, integrations, and data flows end to end until you can explain how a system actually works.
• Design and build agentic AI solutions for platform, delivery, and operations work: identify the toil worth automating, then build, evaluate, and harden the agent that removes it.
• Build security and compliance into the delivery path: least-privilege access, secrets handling, policy-as-code guardrails, and audit evidence produced by design rather than assembled under deadline.
• Design, build, and maintain CI/CD pipelines in GitHub Actions and Azure Pipelines that deliver consistent, secure, and repeatable deployments.
• Enable container-based application delivery on Docker and Kubernetes, with a focus on Azure Kubernetes Service and Azure Container Apps.
• Build reusable cloud-native infrastructure, pipelines, and self-service capabilities that support secure and scalable delivery, including AI and ML workloads.
• Develop APIs, automation scripts, and platform integrations that remove repeat manual requests from engineering teams.
• Support and guide application teams through containerization and modern deployment patterns, and debug complex issues across the application, platform, and infrastructure layers.
• Work within agile delivery practices such as Kanban, Scrumban, and sprints to plan and deliver your work transparently.

What You'll Need to Be Successful

• 5-7 years of hands-on experience in Platform Engineering, DevOps, Cloud Infrastructure, Site Reliability Engineering (SRE), or a related discipline, with demonstrated ownership of enterprise-scale cloud platforms and automation initiatives.
• Demonstrates humility, openness to feedback, and a team-first mindset.
• Comfortable with a high level of transparency, surfacing risks and mistakes early.
• Ability to create high-quality technical diagrams and documentation.
• Deep knowledge of agentic AI concepts: agents and tool use, orchestration, context and retrieval, evaluation, guardrails, and the limits of each. This is one of the most important requirements for the role, because every person in Platform Engineering & Operations is expected to become a builder of agentic AI solutions rather than only a user of them.
• Excellent written and verbal English communication skills with the ability to communicate effectively with technical and business stakeholders.
• Demonstrated ability to reverse engineer application architecture: take an unfamiliar application and the infrastructure under it, trace its components, dependencies, and data flows.
• Working fluency in Infrastructure as Code and Configuration as Code. Terraform and Ansible are Evolent's standard tooling.
• A DevOps mindset: you debug complex systems patiently, automate manual work by default, and treat operational excellence as part of the job rather than afterthought.
• Proficiency in a modern language such as Python, Go, or TypeScript, used to build APIs, automation frameworks, and platform integrations.
• A solid grasp of software design principles, testing strategies, and code quality standards, applied to automation and platform code.

Domain Expertise — DevOps

• CI/CD pipeline engineering depth: Experience designing, building, and scaling pipelines in GitHub Actions and Azure Pipelines, including branching and release strategy, artifact and dependency management, and automated quality and security gates.
• Container and artifact management in production: Experience with Docker and Kubernetes on Azure Kubernetes Service and Azure Container Apps, Helm packaging, and GitOps-based delivery with ArgoCD.
• Experience with infrastructure and configuration automation at production scale with Terraform and Ansible, provisioning infrastructure exclusively as code.
• Working knowledge of the Azure services that carry delivery, including Azure Functions, Logic Apps, ACA, and Service Fabric, with a practical grasp of identity, networking fundamentals, and cost awareness.
• Scale and environment context: Experience with production healthcare workloads under HIPAA and SOC 2, where deployment reliability, change discipline, and audit evidence are non-negotiable.

Nice to Have (Preferred)

• Experience applying agentic AI concepts, whether through professional experience, personal projects, academic work, or other relevant initiatives: what it does, the choices you made, what failed, and what you would change.
• Proficiency in a scripting or programming language used for automation and tooling, such as Python, Go, PowerShell, or Bash.
• Experience in a regulated environment, for example healthcare and HIPAA, SOC 2, or similar.
• Familiarity with CNCF projects such as ArgoCD, Kyverno, and KEDA.
• Experience building the delivery path for AI and ML workloads, including the infrastructure and pipelines those workloads depend on.

Certifications (Preferred)

• Relevant Azure certifications (e.g AZ-104, AZ-400, or AZ-305).
• HashiCorp Terraform Associate preferred, or equivalent.
• Certified Kubernetes Administrator (CKA) preferred, or equivalent.

Academic Qualification

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or an equivalent combination of education, training, and experience.

To ensure a secure hiring process we have implemented several identity verification steps, including submission of a government issued photo ID. We conduct identity verification during interviews, and final interviews may require onsite attendance. All candidates must complete a comprehensive background check, in-person I-9 verification, and may be subject to drug screening prior to employment. The use of artificial intelligence tools during interviews is prohibited and monitored. Misrepresentation will result in immediate disqualification from consideration.

Mandatory Requirements:

Employees must have a high-speed broadband internet connection with a minimum speed of 50 Mbps and the ability to set up a wired connection to their home network to ensure effective remote work. These requirements may be updated as needed by the business.

Evolent is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability status. If you need reasonable accommodation to access the information provided on this website, please contact [email protected] for further assistance.

The expected base salary/wage range for this position is $. As part of our total compensation package, Evolent is proud to offer comprehensive benefits (including health insurance benefits) to qualifying employees. All compensation determinations are based on the skills and experience required for the position and commensurate with experience of selected individuals, which may vary above and below the stated amounts.