Architect and operate secure, multi-environment infrastructure across Azure, Azure Gov, and AWS.
Build GitOps pipelines and reusable OpenTofu (Terraform-compatible) modules with strong CI validation.
Operate Kubernetes platforms (including Helm) and improve reliability through SLOs, postmortems, and automation.
Build observability with Grafana and modern telemetry (metrics, logs, traces, and alerting).
Operate edge networking plus IoT and streaming pipelines (including AWS IoT and Kinesis) for remote sensor data.
Support secure ML workloads and strengthen platform security across identity, secrets, policy, hardening, and compliance controls.

7+ years in infrastructure/platform/SRE roles with direct ownership of production systems.
Deep Azure experience, including high-security and regulated environments (Azure Government strongly preferred).
Practical AWS experience, especially with IoT services, Kinesis, and event/stream-processing architectures.
Expert-level Kubernetes operations experience and strong Helm experience.
Strong GitOps background and a track record improving delivery safety and speed.
Strong infrastructure-as-code expertise with OpenTofu/Terraform and policy-oriented workflows.
Strong observability experience with Grafana and modern telemetry practices.
Experience with edge networking, distributed edge deployments, and remote sensor telemetry pipelines.
Experience supporting ML/AI workloads and secure data processing at cloud and edge.
Demonstrated security depth in IAM, network segmentation, zero trust, secrets management, encryption, and policy as code.
Clear evidence of automation-first thinking and comfort with AI-augmented engineering workflows.
Nice to Have: Experience with FedRAMP, NIST 800-53, CMMC, IL4/IL5, or similar frameworks.
Experience with service meshes, policy engines (for example, OPA/Gatekeeper), workload identity, and software supply chain controls (for example, SBOM practices).
Experience with multi-cluster or hybrid cloud/edge Kubernetes topologies.

Build systems that produce work: prioritize durable platforms and workflows over one-off heroics.
Automation first: eliminate repetitive manual operations through code, policy, and self-service tooling.
AI-augmented execution: actively use and improve AI-assisted workflows for infrastructure design, operations, troubleshooting, and developer productivity.
Safe agency: create clear guardrails, defaults, and feedback loops so engineers can move quickly with confidence.
Empower engineering users: build self-service platform capabilities, paved roads, and documentation that reduce friction and accelerate delivery.

Senior Internal Infrastructure Engineer

Key skills