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Open nowPosted 107 days ago

Infrastructure / DevOps Engineer

discernis6 open roles

Pay
$140,000 – $180,000 a yearly
Where
New York City, NY
Work mode
On site
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Your applicationOpen nowInfrastructure / DevOps Engineerdiscernis · New York City, NY

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 107 days ago

The posting

Infrastructure / DevOps Engineer

About Discernis Discernis builds AI driven document intelligence for high stakes legal work. Because our customers handle privileged and regulated matters that most cloud AI cannot touch, we run on premises and in customer controlled environments as well as in the cloud. That makes security, reliability, and reproducibility core product features, not afterthoughts. We work with AmLaw firms and enterprise legal teams where accuracy, explainability, and data control are non negotiable.

The Role You will own the infrastructure that runs our platform in three very different places: our cloud, customer managed cloud accounts, and customer controlled hardware, including air gapped and on premises environments. The hard and interesting part of this job is making the same product deploy reliably and reproducibly on machines we do not operate. If you like turning bespoke deployments into a repeatable system, this is that job.

What You Will Do

  • Package and ship our platform as a reproducible Kubernetes based bundle that installs cleanly on customer controlled and on premises hardware
  • Operate and improve Kubernetes clusters running both application services and GPU accelerated AI workloads
  • Own our infrastructure as code and release process so environments are reproducible across cloud and on prem
  • Build production grade monitoring, logging, and alerting that works even in restricted customer environments
  • Support large scale search and data infrastructure running on Kubernetes
  • Drive best practices in networking, secrets management, certificate handling, and security hardening

What You Bring

  • Solid experience running production Kubernetes
  • Experience with infrastructure as code tools such as Helm, Terraform, or Pulumi
  • Hands on experience designing CI and CD workflows
  • Comfort with observability stacks and production monitoring
  • Strong networking and Linux fundamentals
  • Bonus: GPU and AI workloads in Kubernetes, NVIDIA drivers and CUDA on bare metal, or shipping software into air gapped or customer controlled environments
  • Bonus: Elasticsearch or similar distributed data systems

Tech Environment Kubernetes and K3s, Docker, NVIDIA GPUs, Elasticsearch, Terraform and Helm, CI/CD tooling, cloud and on premises environments

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