Cloud Platform Architect, TetraScience

• 7+ years in DevOps, Cloud Engineering, or Platform Engineering roles, with at least 2 years in a senior or lead capacity
• Deep, daily-driver coding experience:,programmatically managing infrastructure through Python, APIs and IaC tools is second nature to you. The web console is an afterthought
• Strong production AWS experience: compute (EKS, ECS, EC2), networking (VPC, Transit Gateway, ALB/NLB, Route53), storage (S3, EBS, EFS), security (IAM, KMS, Security Hub, GuardDuty)
• Designed and built CI/CD pipeline infrastructure (not just consumed existing pipelines). GitHub Actions, GitLab CI, or Jenkins at scale
• Container orchestration: ECS, Docker, Kubernetes (EKS preferred), service mesh concepts
• Scripting and automation: Python or Go. Bash only is not enough
• Git-based workflows, branch strategies, and pull-request-driven infrastructure changes
• Experience designing and operating resilient and scalable cloud solutions
• Experience operating in a regulated or compliance-sensitive environment (GxP, SOC2, HIPAA, FedRAMP, or similar)
• Cost optimization: resource tagging strategies, FinOps practices in aws
• Deep, hands-on AWS experience: Serverless Architecture, EKS/ECS, VPC/networking, IAM, KMS, CloudWatch, Lambda, S3, EC2, Kinesis, Athena, Glue, CloudTrail, CostExplorer. You understand Well-Architected Framework principles and apply them daily, not as a checklist exercise
• Databricks experience is strongly preferred

Desirable

• Own the cloud infrastructure, CI/CD systems, and deployment automation for TetraScience’s multi-tenant SaaS platform serving global biopharma customers
• This is a hands-on technical lead role. You will lead through technical depth and influence across teams. Strong architecture and implementation skills are important for success in this role
• You will evolve our cloud architecture, build substantial parts of it in Python, CloudFormation and Terraform. You will architect and build deployment pipelines to AWS and Databricks, and drive the engineering practices that determine how fast and safely we ship software
• Own, design, build, and maintain the cloud infrastructure using Cloudformation, Terraform and custom Python glue
• Every environment is provisioned and governed through code. Architect the deployment pipeline infrastructure end to end. GitHub Actions, CodeBuild, container image pipelines, code scanning, artifact registries, pre-merge integration environments, promotion gates, and automated rollback
• Your goal: engineers merge code and it reaches production safely without manual intervention
• You will partner with other 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
• DevSecOps Embed security into the product and pipelins: 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
• Production monitoring, alerting, log aggregation, and incident response infrastructure. Support for developer teams. Blameless postmortem culture
• Current Tech Stack:
• Cloud: AWS
• IaC: Terraform, CloudFormation
• CI/CD: GitHub Actions
• Containers: Docker, ECS
• Languages: Python, Bash
• Data: PostgreSQL / Aurora, S3 data lake, Databricks (Lakehouse)