Technology Lead, 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 Terraform experience: modules, workspaces, 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, 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: Docker, Kubernetes (EKS preferred), Helm charts, service mesh concepts
• Scripting and automation: Python, Bash, or Go for tooling and glue code
• Git-based workflows, branch strategies, and pull-request-driven infrastructure changes
• Experience operating in a regulated or compliance-sensitive environment (GxP, SOC2, HIPAA, FedRAMP, or similar)

Desirable

• As DevOps Lead you will 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, 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
• Infrastructure as Code
• Design, 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 Architecture
• Own the build, test, and deployment pipeline infrastructure end to end. GitHub 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 Engineering
• Deep, hands-on AWS work: EKS/ECS, VPC architecture, IAM, KMS, CloudWatch, 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
• DevSecOps
• Embed 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 Velocity
• Partner 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 Reliability
• Production monitoring, alerting, log aggregation, and incident response infrastructure. Datadog, Prometheus/Grafana, or equivalent. On-call participation and blameless postmortem culture
• TetraScience 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
• Current Tech Stack
• Cloud - AWS (primary), Azure (customer deployments)
• IaC - Terraform, CloudFormation (legacy stacks)
• CI/CD - GitHub Actions
• Containers - Docker, ECS, EKS
• Observability - Datadog
• Languages - Python, Bash
• Data - PostgresSQL/Aurora, S3 data lake, Databricks (Lakehouse)