Senior DevOps / MLOps Engineer

About this role

Role Overview:

You will own the Azure platform behind SimpliGov’s AI-native delivery model—infrastructure, Kubernetes, networking, observability, AI serving, and cost discipline. This is hands-on production engineering within a FedRAMP-conscious environment, where security, auditability, and reliability are core responsibilities.

Responsibilities:

• Deploy and operate our Azure platform: AKS, networking, identity, storage, and environments from development through production

• Own infrastructure as code end to end: environments are reproducible, drift is detected, and nothing reaches an environment without platform visibility

• Operate the AI infrastructure layer: self-hosted observability and evaluation tooling (Langfuse), product telemetry, model gateway and per-workload routing, and compliant GovCloud inference paths

• Own cloud and AI cost: metering, budgets, unit economics, MACC drawdown strategy, and active remediation; cost is an engineering metric here, not a finance afterthought

• Harden production access and controls: least privilege, secrets management, audit evidence, and a FedRAMP-conscious security posture

• Partner with AI Operations on the deploy-and-release path: Octopus Deploy, environment promotion, progressive rollout, and rollback

• Build platform reliability: monitoring, alerting, incident response, and capacity planning

• Give the microservices decomposition the platform primitives it needs: service infrastructure, scaling patterns, and clean environment boundaries

Qualifications:

• 5+ years in DevOps, platform engineering, or site reliability engineering in SaaS environments

• Deep Azure experience: AKS, networking, identity (Entra), and monitoring; you have run production Kubernetes

• Infrastructure as code as your default (Terraform, Bicep, or similar), plus strong scripting; you automate before you document

• MLOps experience: deploying and operating LLM or ML systems in production, including model gateways, ...