Tech Stack
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonTerraform
About the role
- Lead the technical workstreams for enterprise customer implementations across cloud, hybrid, and on-prem environments
- Serve as the key technical partner during pre-sales: shape solutions, lead POC implementation, and collaborate with Sales and Scientific Development
- Assess complex customer environments, identify gaps, and recommend improvements (infrastructure configuration, automation, cloud cost-efficiency)
- Lead deep-dive technical reviews and clearly communicate findings and solutions to engineers and decision-makers
- Build and maintain tooling to simplify deployment, strengthen automation, and improve troubleshooting
- Act as technical backbone for client-facing support: spot patterns, surface systemic problems, and liaise with internal teams (DevOps & Engineering) to drive fixes
Requirements
- 5+ years of experience in a technical solutions or architecture role, ideally customer-facing and focused on system integration and infrastructure deployments
- Maintain a public code portfolio (GitHub, GitLab, etc.) and include a link when applying
- Real-world Python projects: tools / integrations / backends (not just scripts)
- Use of Docker and/or Kubernetes for packaging and deployment
- Build or integrate with external APIs over HTTPS (3rd party or self-hosted)
- Infrastructure as Code – preferably with Terraform
- Experience building and shipping production systems or customer-specific solutions
- Strong cloud-native infrastructure experience, especially on AWS (GCP or Azure are a plus)
- Comfortable debugging across application, infrastructure, and deployment layers
- Experience working directly with customers: mapping requirements, explaining systems to engineers and stakeholders
- Curious, resourceful, and persistent in untangling complex technical environments
- Bonus: experience in fast-moving startups
- Bonus: experience in technical pre-sales and/or Life Sciences
- Bonus: background in Life Sciences environments or scientific computing workflows