DevOps Engineer

Pivotly builds B2B software that helps businesses move faster. Our two products — Pivotly Parse, an AI-powered document parsing platform with human-in-the-loop verification, and Pivotly Core, an integration platform connecting ERPs, CRMs, and quoting tools — are used by teams that can't afford operational drag. We're a lean, ambitious team building infrastructure that matters. Role Overview We're looking for a Senior DevOps Engineer to own our infrastructure end-to-end. You'll work closely with the engineering team to build reliable, scalable systems for two distinct product lines — one with heavy AI workloads, one with complex integration pipelines. This is a hands-on role with real ownership: you'll set the direction for our CI/CD, cloud infrastructure, observability stack, and security posture. What You’ll Do Design, build, and maintain scalable cloud infrastructure on Azure (primary) with awareness of multi-cloud considerations Own CI/CD pipelines end-to-end — from commit to production — using Azure DevOps Manage containerized workloads with Docker and Kubernetes; optimize for reliability and cost Implement and maintain observability tooling: logging, metrics, alerting, and on-call runbooks Harden security posture: secrets management, network policies, access controls, and compliance readiness Support AI/ML infrastructure needs for Pivotly Parse — GPU scheduling, model deployment, Python Runner environments Build out infrastructure-as-code practices (Terraform or Bicep) and drive adoption across the team Collaborate with engineers to diagnose production issues and reduce toil through automation Own the incident response process and drive post-mortems with actionable follow-through What We’re Looking For 5+ years in a DevOps, SRE, or infrastructure engineering role Deep hands-on experience with Azure and Azure DevOps Strong Kubernetes and container orchestration skills in production environments Proficiency in infrastructure-as-code; Terraform preferred Solid scripting ability in Python or Bash for automation Experience supporting Python-based application environments and async workloads Track record of improving reliability metrics (uptime, deployment frequency, MTTR) Strong communicator — comfortable working async across time zones with minimal hand-holding Nice to Have Experience with AI/ML infrastructure — model serving, GPU scheduling, or data pipeline orchestration Familiarity with ERP/CRM integration environments and the data flows they generate Background in B2B SaaS or platform engineering Experience with cron-based and event-driven scheduling systems Work Location: Remote