Remote Senior MLOps Engineer — Azure Platform Lead

Jobot; Atlanta (GA); Remote; USD 150,000 - 175,000; Full time

Benefits offered by this job

100% work from home (US based only)

Own platform ownership and cost focus

Competitive base, bonus, and equity

Medical, dental, and vision insurance

Disability insurance

11 Paid holidays

Flexible time off

401k plan with 4% employer match

Monthly stipend for home office

Monthly wellness stipend

Job summary

Jobot is seeking an experienced DevOps/Platform Engineer to own the Azure-based platform and its cost discipline for a government-focused AI SaaS. You will deploy, operate, and scale the platform across AKS, networking, identity, and observability while ensuring least-privilege security and auditability.

You will collaborate with AI Ops, own the infrastructure as code lifecycle, and drive production readiness with strong emphasis on compliance, governance, and cost controls.

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, 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

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

Skills

DevOps

Platform engineering

Site reliability engineering

MLOps

Cost optimization

FedRAMP compliance

Kubernetes

Azure/AKS

Infrastructure as code

SaaS

Tools

Terraform

Bicep

Langfuse

Octopus Deploy

GovCloud / Azure Gov

Job description

Jobot is seeking an experienced DevOps/Platform Engineer to own the Azure-based platform and its cost discipline for a government-focused AI SaaS. You will deploy, operate, and scale the platform across AKS, networking, identity, and observability while ensuring least-privilege security and auditability.

You will collaborate with AI Ops, own the infrastructure as code lifecycle, and drive production readiness with strong emphasis on compliance, governance, and cost controls.