Devops Engineer

Uncountable Inc.

Job Overview

Location

New York, San Francisco, Munich or London

Job Type

Full-time

Full Job Description

📋 Description

• Own end-to-end deployment of the Uncountable Web Platform into Fortune-500 customer VPCs, acting as the single point of accountability for uptime, security, and performance in each environment.
• Architect repeatable, auditable automation that turns weeks-long manual provisioning cycles into one-click releases, leveraging Infrastructure-as-Code tools such as Terraform, CloudFormation, or Pulumi.
• Partner directly with customer IT, security, and networking teams to translate enterprise-grade requirements—VPN peering, private subnets, IAM boundaries, and compliance controls—into concrete deployment blueprints that satisfy both Uncountable’s SaaS standards and each client’s regulatory landscape.
• Continuously harden the internal CI/CD backbone (GitHub Actions, Argo CD, or similar) so that every code change is built, tested, scanned, and promoted through dev, staging, and production with zero-downtime blue/green or canary strategies.
• Instrument observability from day one: design Prometheus/Grafana dashboards, distributed tracing with OpenTelemetry, and centralized logging (ELK, Loki, or Datadog) that surface actionable alerts before customers notice an issue.
• Optimize cloud spend across AWS, Azure, or GCP by rightsizing clusters, leveraging spot instances, and implementing auto-scaling policies that keep compute costs predictable while handling bursty R&D workloads.
• Build self-service tooling that empowers software engineers to spin up ephemeral test environments in minutes, complete with seeded data sets and security guardrails, accelerating the feedback loop for new features.
• Lead blameless post-mortems and reliability reviews, turning incidents into iterative improvements that raise the bar for SLOs, error budgets, and disaster-recovery objectives.
• Contribute to the security posture by automating CIS benchmark compliance, secrets management (Vault, AWS KMS, or SSM), and vulnerability scanning in both container images and running clusters.
• Champion DevOps culture across the company: run internal workshops, write runbooks, and mentor junior engineers so that “you build it, you run it” becomes second nature.
• Stay ahead of the curve by evaluating emerging technologies—Kubernetes operators, service meshes, eBPF, or confidential computing—and piloting those that deliver measurable value to our industrial R&D customers.
• Report directly to the Head of Engineering and collaborate daily with product managers, data scientists, and frontend/backend teams to ensure infrastructure decisions accelerate—not hinder—innovation.

🎯 Requirements

• 2+ years of hands-on development or DevOps experience shipping and maintaining production cloud applications
• Deep familiarity with at least one major cloud provider (AWS, Azure, or GCP) and core services such as VPC, IAM, EKS/GKE/AKS, RDS, and S3
• Solid computer-science fundamentals—data structures, algorithms, and distributed-systems concepts—and a B.S. in Computer Science or equivalent practical experience
• Demonstrated success automating infrastructure with IaC tools (Terraform, CloudFormation, Pulumi, or CDK) and container orchestration platforms (Kubernetes, ECS, or OpenShift)
• Nice-to-have: experience working with regulated or high-compliance environments (SOC 2, ISO 27001, HIPAA, or GxP) and scripting proficiency in Python, Go, or Bash

🏖️ Benefits

• Competitive base salary of $120K–$160K plus meaningful equity in a fast-growing, venture-backed company
• Comprehensive health and dental insurance for you and eligible dependents
• 401(k) plan with employer contribution to help you build long-term wealth
• Flexible on-site presence in New York, San Francisco, Munich, or London, giving you access to vibrant tech hubs while maintaining work-life balance

Skills & Technologies

DevOps

Onsite

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Uncountable Inc.

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About Uncountable Inc.

Uncountable provides a cloud-based R&D data platform that helps materials, chemicals, and life-science manufacturers replace scattered spreadsheets and siloed lab notebooks with a unified, searchable system. The software structures experimental results, links formulations to performance data, and applies machine-learning models to predict outcomes, accelerating formulation cycles and reducing trial-and-error lab work. Teams use the platform to design experiments, capture measurements, share knowledge, and generate regulatory reports while maintaining full data traceability and version control across global research sites.

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