SandboxAQ is seeking a backend engineer generalist to contribute to their drug discovery and chemistry simulation platform, aiming to solve challenges in life sciences and chemistry simulation.
Requirements
- 3+ years of experience with Python with knowledge of software design principles and architectural patterns.
- Comfort writing clean, readable, well-tested, maintainable code.
- Experience with at least one major cloud provider. GCP preferred.
- Experience with building REST APIs and knowledge of best practices.
- Knowledge of cloud orchestration technologies like K8s or batch-type systems as well as workflow management tools (Airflow or similar)
- Knowledge of database systems and related concepts: ORMs, schemas, and transactional vs. analytic systems.
- Exposure to Terraform or another IaC system, along with DevOps and GitOps.
- Knowledge of CI/CD best practices and building CI/CD pipelines.
Responsibilities
- Contribute to the development of SandboxAQ’s chemistry and life sciences simulation platform.
- Work closely with users and members of the product team to measure the impact of the code you develop on users, gather feedback, and iterate on your software.
- Participate in planning, design, and sprint ceremony meetings.
- Embed closely with R&D teams to assist in delivering project goals and drive adoption of practices and tooling.
- Collaborate closely with the product team and internal stakeholders in all phases of software development to validate the solutions you propose and implement.
- In collaboration with the rest of the engineering team, build and manage infrastructure for SandboxAQ’s simulation and data platform.
- Review code and participate in design and architectural discussions.
Other
- Excellent communication and collaboration skills, with the ability to effectively influence a cross-functional team.
- You’re entrepreneurial and customer-obsessed.
- Most importantly, you’ll bring a track record of working in a fast-moving software development team, exploring new technologies, and solving problems across an entire software stack.
- Domain experience in advanced materials, drug discovery, cheminformatics, or other areas of chemistry or biology, especially experience with AI systems applied to these domains.
- Delivering scientific code for R&D projects, especially in the simulation and numerical optimization domains
