Software Engineer II, Computational Platform

Dyno Therapeutics is a high-energy team dedicated to building high-performance genetic technologies that transform patient lives. They are seeking a Software Engineer II to build and maintain AI products, driving the development of cloud infrastructure and implementing tools for scientists and partners in genetic medicine.

Responsibilities:

• Drive engineering quality and reliability of Dyno’s external-facing AI products such as design.dynotx.com
• Enable scaling of AI product workflows on design.dynotx.com to handle thousands of simultaneous workflows
• Translate scientific and clinical questions into production-ready systems, including APIs, pipelines, and user-facing tools
• Implement a sound data platform for generation, processing, and serving AI data, ensuring access, security, and data lifecycle integrity
• Move quickly from prototype to production, balancing speed with reliability
• Work with urgency and adaptability, balancing innovation with execution
• Collaborate cross-functionally, leveraging Dyno’s high-trust, high-impact culture to drive results

Requirements:

• 4+ years of software engineering experience in industry
• Strong software development best practices: deployment, code management, environment management, and security
• Hands-on cloud engineering experience with GCP and/or AWS, including Terraform, Kubernetes/Docker, and basic cloud networking and security
• Solid experience with data engineering, including relational databases and data modeling
• Experience taking agentic AI products to market or contributing to production-grade AI-driven applications
• Expertise in Python or a similar programming language
• React/Javascript experience
• Alignment with Dyno's core values - We seek individuals who step up when things get tough, recalibrate when priorities shift, and thrive in a high-expectation environment
• A proactive, problem-solving mindset - you don't just identify challenges; you find solutions
• Biotech or life sciences domain experience
• Experience with LLMs, agent-based systems, or modern AI workflows
• Experience with software lifecycle best practices and DevOps
• Familiarity with ETL system design and best practices
• Experience writing and optimizing SQL queries
• Experience with the current landscape of database and data processing technologies