Senior DevOps / MLOps Engineer

SimpliGov LLCBaltimore, MD
$150,000

About The Position

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. 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.

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
  • Comfortable holding production access, with the discipline that implies

Nice To Haves

  • Experience in compliance-heavy environments (FedRAMP, StateRAMP, SOC 2, or similar) is a strong plus

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

Benefits

  • Medical, dental, and vision insurance plans, with significant employer contributions for employees AND dependents
  • Company-sponsored life/disabilities insurances
  • 11 Paid holidays
  • Flexible time off
  • 401k plan with 4% employer match
  • Monthly stipends for wellness and home office expenses
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