Senior DevOps / MLOps Engineer

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

Requirements

• 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, inference infrastructure, or AI observability stacks
• Demonstrated cost work: you can point to cloud spend you found, explained, and reduced
• Experience in compliance-heavy environments (FedRAMP, StateRAMP, SOC 2, or similar) is a strong plus
• Comfortable holding production access, with the discipline that implies

Skills

• Treats environment integrity as sacred: no invisible changes, no snowflake servers, no heroics that cannot be audited
• Cost literacy: reads a cloud bill the way an engineer reads a stack trace
• Automates first: your instinct is a pipeline or a policy, not a runbook step
• Thinks in the open: surfaces risk early and documents what you build
• Calm in production incidents; rigorous in the postmortem

About the role

This is not a ticket-queue operations role and not a NOC seat. If your model of DevOps is executing change requests that other people design, this is not the fit. It is also not a research MLOps role: the AI infrastructure here serves a shipping product for government customers, with the reliability and compliance expectations that implies.

We run an AI-native product development lifecycle. Autonomous agents participate in planning, coding, validation, and release; humans own judgment, standards, and direction. Work moves through a Plan-and-Review cadence rather than ceremony-heavy Agile. Two standards are non-negotiable: you own and can explain everything you ship, no matter what produced it, and you think in the open, surfacing uncertainty early rather than burying it.

Benefits

• Medical, dental, and vision insurance plans, with significant employer contributions for employees AND dependents (contributions based on base-level plan; buyup plans available at additional costs)
• Company-sponsored life/disabilities insurances
• Paid holidays
• Flexible time off
• 401k plan with 4% employer match
• Monthly stipends for wellness and home office expenses

Pay

The US base salary range for this full-time position is approximately $160,000.00 - $190,000.00 + bonus + benefits. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.