Principle Systems Engineer

About the Role

We are hiring a Principal Platform Engineer to help build and scale our Azure-native cloud platform as we migrate services from an on-premises data center to the cloud. This is a hands-on engineering role with a strong mentoring component -- you will design and build alongside the team while raising the technical bar for engineers earlier in their careers. You will work across infrastructure, deployment automation, observability, and security tooling, with exposure to both legacy automation modernization and net-new platform capability.

This is an individual contributor role. You will not have direct reports, but you will be expected to mentor and provide technical guidance to junior and mid-level engineers on the team, including reviewing designs, pairing on complex problems, and setting technical direction by example.

What You'll Do

· Design and build Azure infrastructure using a cloud native approach, leveraging managed services wherever they meet reliability and cost requirements.

· Lead technical execution of the migration of services from an on-premises data center to Azure, including dependency mapping, migration sequencing, and cutover risk management.

· Operate and extend our AKS-based platform, including GitOps deployment patterns, namespace isolation, and policy enforcement.

· Own and evolve reusable Terraform modules that other engineering teams consume, with clear interface contracts between platform-owned and application-owned infrastructure.

· Build and maintain observability coverage (metrics, logs, alerting) so that platform and application health are measurable and actionable, not just instrumented.

· Apply policy-as-code to enforce security, compliance, and operational standards across the platform, and reduce reliance on manual review gates.

· Design and review Identity and Access Management patterns, including workload identity, least-privilege access models, and secrets management -- with a clear bias away from static credentials.

· Participate in business continuity and disaster recovery planning for platform services, including failover design, RTO/RPO definition, and recovery testing.

· Contribute to CI/CD pipeline design and standards used across engineering teams building on the platform.

· Use AI-assisted engineering tools (e.g., Claude Code, GitHub Copilot, or equivalent) as part of the standard workflow, and evaluate where AI-driven platform capabilities (automated remediation, intelligent alerting, natural-language operational tooling) can be responsibly introduced into the platform itself.

· Mentor junior and mid-level engineers through code/design review, pairing, and informal technical coaching. Help less experienced engineers build sound judgment around idempotency, error handling, and migration candidacy when evaluating legacy automation.

Required Qualifications

· 8+ years in platform, infrastructure, or site reliability engineering roles, with demonstrated Principal-level scope (technical leadership without formal management).

· Deep hands-on experience with Azure, building cloud native architectures using managed services rather than defaulting to IaaS.

· Production experience running and operating Kubernetes at scale, ideally AKS specifically.

· Strong GitOps experience (ArgoCD, Flux, or equivalent) -- all infrastructure and cluster changes should trace to a git commit as a matter of practice, not preference.

· Experience leading or significantly contributing to a data center-to-cloud migration, including business continuity and disaster recovery planning.

· Working fluency in policy-as-code tooling (Kyverno, OPA/Gatekeeper, or equivalent) for security and compliance enforcement.

· Strong Identity and Access Management background: workload identity federation, least-privilege IAM design, secrets management patterns that avoid static credentials.

· Experience building and maintaining an observability stack (Prometheus, Grafana, Thanos, or equivalent).

· Solid Terraform experience, including designing reusable modules consumed by other teams, not just single-project usage.

· Practical, current experience using AI-assisted development tools in daily engineering work.

· Demonstrated ability to mentor other engineers -- through review, pairing, or informal technical leadership -- without formal authority.

Preferred Qualifications

· Experience designing or operating hub-and-spoke network architectures in Azure.

· Familiarity with CI/CD pipeline design for multi-team, multi-repo environments (e.g., GitHub Actions-based runner infrastructure).

· Exposure to evaluating or building genuinely AI-driven operational tooling (as distinct from rules-based automation mislabeled as AI).

· Experience presenting technical tradeoffs to both engineering and business stakeholders.

Altera

A global healthcare IT innovator, Altera Digital Health develops and elevates technology to connect and inspire healthier communities. Our platform approach to our solutions is changing the way healthcare is delivered. By keeping the human user at the center of our design methodology, we are supporting caregivers and helping patients meet and exceed their wellness goals. Together, with our clients, we’re driving a new era of healthcare.

Altera is an Equal Opportunity/Affirmative Action Employer. We consider applicants without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, or membership in any other group protected by local law.

If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at:

HR.Recruiting@AlteraHealth.com

To learn more, visit www.alterahealth.com.

Our commitment to fair and equitable hiring. As part of our recruitment process, we use artificial intelligence (AI) tools during the initial screening phase to help identify candidates whose qualifications most closely align with the requirements of the role. This technology supports efficiency and consistency in the early stages, but it never replaces human judgement. All subsequent evaluations and final hiring decisions are made by our recruitment professionals. AI does not make final hiring decisions.