Software Engineer II, Computational Platform

Dyno Therapeutics is a high-energy team focused on building transformative genetic technologies. The Software Engineer II will develop and maintain AI products, ensuring they are reliable and scalable while collaborating with scientists and partners in the field of 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