Cloud Platform Architect, Tech Lead
Listed on 2026-06-03
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IT/Tech
Cloud Computing, Systems Engineer
About Tetra Science
Tetra Science is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. Tetra Science’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
In connection with your candidacy, you will be asked to carefully review authored "The Tetra Way" by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.
As Dev Ops Lead you will own the cloud infrastructure, CI/CD systems, and deployment automation for Tetra Science’s multi‑tenant SaaS platform serving global biopharma customers. This is a hands‑on technical lead role, not a people manager title. You will write IaC daily, architect deployment pipelines, and drive the engineering practices that determine how fast and safely we ship software.
What you’ll Own Infrastructure as CodeDesign, build, and maintain all cloud infrastructure using Terraform (primary) across AWS and Azure. Every environment, from sandbox to production, is provisioned and governed through code. You treat infrastructure PRs with the same rigor as application PRs: peer review, automated validation, drift detection, state management.
CI/CD ArchitectureOwn the build, test, and deployment pipeline infrastructure end to end. Git Hub Actions, container image pipelines, artifact registries, pre‑merge integration environments, promotion gates, and automated rollback. Your goal: engineers merge code and it reaches production safely without manual intervention.
Cloud EngineeringDeep, hands‑on AWS work: EKS/ECS, VPC architecture, IAM, KMS, Cloud Watch, Lambda, S3, and networking. Azure fluency for customer‑facing deployments. You understand Well‑Architected Framework principles and apply them daily, not as a checklist exercise.
Dev Sec OpsEmbed security into the pipeline: container image scanning, SAST/DAST integration, secrets management, least‑privilege IAM, and compliance‑as‑code. You work in a GxP‑regulated environment where auditability and traceability of deployments are non‑negotiable.
Release VelocityPartner with engineering teams to reduce cycle time from commit to production. Instrument pipeline metrics (build time, deployment frequency, change failure rate, MTTR). Identify and eliminate bottlenecks. Build self‑service capabilities so product teams are not blocked by infrastructure.
Observability and ReliabilityProduction monitoring, alerting, log aggregation, and incident response infrastructure. Datadog, Prometheus/Grafana, or equivalent. On‑call participation and blameless postmortem culture.
Why This Role MattersTetra Science is building the data and AI platform for drug development. Our customers are global pharma companies running regulated scientific workloads. The infrastructure you build determines whether we ship features weekly or monthly, whether customer environments are secure and compliant by default, and whether the platform scales from tens to hundreds of enterprise deployments. Release velocity is a company‑level strategic priority, and this role is at the center of it.
- 7+ years in Dev Ops, Cloud Engineering, or Platform Engineering roles, with at least 2 years in a senior or lead capacity
- Deep, daily-driver Terraform experience: modules, work spaces, state backends, provider configuration, CI‑driven plan/apply workflows. This is the core technical screen.
- Strong production AWS experience: compute (EKS, ECS, EC2), networking (VPC, Transit Gateway, ALB/NLB, Route
53), storage (S3, EBS, EFS), security (IAM, KMS, Security Hub, Guard Duty) - Designed and built CI/CD pipeline infrastructure (not just consumed existing pipelines). Git Hub Actions, Git Lab CI, or Jenkins at scale.
- Container orchestration:
Docker, Kubernetes (EKS preferred), Helm charts, service mesh concepts - Scripting and automation:
Python, Bash, or Go…
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