Full Stack Developer

Responsibilities

• Drive design and implementation of AI agent solutions that automate data analysis and decision workflows within bioinformatics platforms to improve scientific insight and operational efficiency.
• Lead the development of robust Python based services and tools that process complex biological datasets ensuring accuracy scalability and maintainability for production use.
• Architect and optimize relational database structures using SQL PL SQL and mySQL to support high volume genomic and clinical data storage retrieval and transformation activities.
• Guide the creation and enhancement of Net Core applications that expose bioinformatics functionalities through secure reliable and performant application programming interfaces and user facing services.
• Coordinate integration of AI agents with existing laboratory systems and research applications ensuring seamless data exchange and consistent business logic across the bioinformatics ecosystem.
• Apply Azure cloud capabilities including data services compute and monitoring to deploy and operate AI and data processing workloads with strong reliability and cost awareness.
• Establish coding patterns testing practices and documentation standards that keep the technical stack consistent reduce defects and enable smooth onboarding for future team members.
• Collaborate closely with bioinformatics experts data scientists and stakeholders to translate domain specific requirements into clear technical tasks and measurable delivery milestones.
• Perform code reviews and technical validation of Python SQL and Net Core components to ensure compliance with security performance and regulatory expectations relevant to healthcare data.
• Troubleshoot complex production issues across application data and cloud layers applying structured analysis to restore service quickly and prevent recurrence through targeted improvements.
• Mentor junior engineers on AI agent patterns database usage and clean coding principles helping build a strong technical culture that supports innovation in life sciences solutions.
• Document solution architectures data flows and operational procedures in a clear and accessible manner so cross functional teams can safely operate and extend the platforms.
• Coordinate with project and product teams to plan releases estimate effort and prioritize features that deliver maximum value to researchers clinicians and patients through improved digital tools.