Senior MLOps Engineer

"Want to learn more about this role and Jobot? Click our Jobot logo and follow our LinkedIn page! Job details Own where changes land and what it costs to run This Jobot Job is hosted by Charles Simmons Are you a fit? Easy Apply now by clicking the ""Easy Apply"" button and sending us your resume. Salary $150000 - $175000 per year A bit about us Small mid staged AI native SaaS startup helps state and local governments modernize paper-based processes into intelligent AI-driven digital workflows. As we evolve into an AI-first platform our development velocity model iteration frequency and cross-team complexity increase. A reliable cost-disciplined platform is essential to scale safely and predictably. Why join us? 100% work from home (US based only) Own the platform that build validation and release loops run on and deploy to infrastructure environments Kubernetes Networking observability and the AI serving and routing layer. Competitive base bonus and equity options 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 short-term and long-term disability insurance 11 Paid holidays Flexible time off 401k plan with 4% employer match Monthly stipend for home office expenses Monthly wellness stipend Job Details Everything runs on Azure and the platform is getting more interesting an AI product suite heading toward general availability self-hosted AI observability and telemetry inside a FedRAMP-conscious boundary autonomous agents participating in delivery and a microservices decomposition in flight. You will deploy operate and scale that platform and you will own its cost discipline. This is a production seat with production access and we treat that as an engineering responsibility not a badge least privilege audit trails and environment integrity are part of the job because our customers are governments. You will work alongside our AI Operations Engineer who owns the agentic delivery system (the loops that build validate and release code). You own the platform those loops run on and deploy to infrastructure environments Kubernetes networking observability and the AI serving and routing layer. The boundary is simple they own how changes move you own where changes land and what it costs to run.

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 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

Key Competencies

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 What This Role Is NOT 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. How We Work 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. Interested in hearing more? Easy Apply now by clicking the ""Easy Apply"" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race color sex sexual orientation gender identity religion national origin age (40 and over) disability military status genetic information or any other basis protected by applicable federal state or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal state or local law regarding criminal backgrounds including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. Information collected and processed as part of your Jobot candidate profile and any job applications resumes or other information you choose to submit is subject to Jobot's Privacy Policy as well as the Jobot California Worker

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