Key Responsibilities

Backend Development & System Design

• Design and develop scalable backend services for HPC-driven drug discovery workflows
• Build and maintain distributed systems supporting large-scale compound modeling
• Develop APIs and client-server systems using Python and Go

Performance & Optimization

• Optimize compute and storage systems for high-performance scientific workloads
• Improve database performance and schema design for large-scale datasets
• Support billions of in-silico compound evaluations efficiently

Testing & Quality Engineering

• Implement unit, integration, and end-to-end testing frameworks using pytest and other tools
• Participate in CI/CD pipelines, code reviews, and automated deployment workflows
• Ensure system reliability through robust debugging and troubleshooting

Data & Infrastructure Engineering

• Work with PostgreSQL and SQLite for relational data modeling and optimization
• Design and manage database structures for scientific and computational data
• Work with containerized environments using Docker and cloud platforms like AWS

Collaboration & Scientific Integration

• Collaborate with scientists, product designers, and cross-functional engineering teams
• Translate scientific requirements into scalable software solutions
• Support life sciences workflows and computational chemistry applications