Description

Design and implement scalable, cloud-based solutions for scientific informatics and predictive sciences.

This role is on-site.

Responsibilities

• Design cloud-native architectures for scientific informatics systems and develop strategic roadmaps.
• Guide engineering teams through technical implementation and lead early-stage prototypes into production.
• Integrate LLM-based AI capabilities (OpenAI, Claude, Gemini, LLaMa) into existing cloud solutions.
• Optimize cloud performance, cost, and scalability while ensuring robust monitoring and testing.

Required Skills

• 10+ years of experience in AWS architecture and LIMS management.
• Expertise with LIMS platforms including Dotmatics, Benchling, and Genedata.
• Hands-on experience with AWS serverless stack: Lambda, SQS, Redshift, DynamoDB, and RDS.
• Proficiency in Python, SQL, and R.
• Experience with React or Angular for front-end integration.
• Experience with Docker, ECS, and cloud-native monitoring tools.
• Background in scientific data systems and AI-driven research solutions.
• Ability to work within Agile methodologies.

Key Skills

Education

Any Graduate