Full-Stack Software Developer

POSITION OVERVIEW

The Full-Stack Software Developer designs, develops, and supports the software systems that run myDNA's CAP/CLIA laboratory operations. This role sits within the Laboratory department and works across the full stack — C#/ASP.NET Core services, React front ends, and SQL Server data layers — to build tools that lab staff depend on for sample tracking, instrument integration, and data integrity. The developer is expected to work in an LLM-assisted development environment, using Claude Code and similar tools as part of the daily workflow for implementation, refactoring, testing, and issue investigation. Effective use of these tools requires strong underlying engineering fundamentals: the ability to decompose problems, recognize a bad design or a subtle defect on sight, and reject output that doesn't meet the bar. The developer remains fully accountable for the correctness, security, and maintainability of everything that ships. Because the systems this role supports handle clinical and consumer genetic data, a high standard of attention to detail, confidentiality, and validation discipline is required. Familiarity with laboratory environments, automation, or genomics is a plus.

ACCOUNTABILITIES AND RESPONSIBILITIES

Software Design & Development- 45%

• Design, build, and ship full-stack solutions supporting laboratory operations using C#/ASP.NET Core, React/TypeScript, RESTful Web APIs, and SQL Server.
• Translate business and lab requirements into functional, maintainable solutions applying SOLID principles, appropriate design patterns, and CQRS where warranted.
• Build and integrate messagingbased workflows (RabbitMQ). Maintain and improve CI/CD pipelines and development tooling.
• Maintain code documentation and contribute to system architecture decisions.

LLM-Assisted Development & Code Quality

• Use Claude Code and comparable AI development tools as a primary part of the daily workflow for implementation, refactoring, test authoring, and investigation.
• Critically review AI-generated output for correctness, security, and maintainability; reject or rework what does not meet standards.
• Participate in peer code review. Retain full accountability for all code that ships regardless of how it was produced.

System Support & Troubleshooting- 15%

• Investigate, triage, and resolve production and development issues affecting laboratory systems
• Collect, analyze, and summarize service issues; identify root cause and implement durable fixes.
• Support lab staff as a technical point of contact.
• Monitor system health and respond to incidents affecting sample processing or data flow.

Requirements & Stakeholder Collaboration- 10%

• Confer with laboratory staff, scientists, and other stakeholders to gather and clarify requirements. Study systems flow, data usage, and work processes.
• Ask questions, make suggestions, and convey technical concepts clearly to non-technical audiences. Participate in UI/UX prototyping and solution validation.

Data Integrity, Security & Compliance- 10%

• Protect operations by maintaining confidentiality of clinical and consumer genetic data and prioritizing security in all design and implementation decisions.
• Ensure changes to laboratory systems preserve data integrity and traceability consistent with CAP/CLIA requirements.
• Follow validation and change-control practices for regulated systems.

POSITION REQUIREMENTS

Skills and Knowledge

• Strong coding skill in C# and JavaScript (TypeScript experience preferred)
• Hands-on proficiency with ASP.NET Core, React, HTML/CSS, and RESTful Web API development.
• Solid SQL skills (primarily SQL Server, some PostgreSQL) and experience with Entity Framework.
• Working knowledge of software design principles (SOLID), object-oriented programming and design, system architecture, CQRS, and messaging systems such as RabbitMQ. Proficient with Git and continuous integration/deployment practices.
• Effective use of LLM-assisted development tools, including Claude Code, as part of the daily engineering workflow.
• Strong engineering fundamentals: the ability to decompose problems clearly, direct AI tooling toward a well-defined outcome, recognize flawed designs or subtle defects on sight, and reject output that does not meet quality standards.
• Strong troubleshooting and analytical skills, with the ability to collect, analyze, and summarize technical issues.
• Clear written and verbal communication, including the ability to DECISION MAKING explain complex technical topics to non-technical stakeholders.
• Demonstrated integrity, dependability, attention to detail, and a commitment to confidentiality and data security.
• Preferred: understanding of genetics, molecular biology, PCR, next-generation sequencing, laboratory automation, liquid handlers, and robotics.

Experience:

• Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• 4+ years of professional software development experience building and maintaining production applications across the full stack.
• Demonstrated experience designing and shipping web applications using C#/.NET and a modern JavaScript framework, backed by relational databases.
• Experience working within a version-controlled, CI/CD-based development process and participating in peer code review.
• Practical experience using AI coding assistants in a production development workflow is preferred, as is experience integrating with third-party systems, instruments, or APIs.
• Preferred: prior experience in a laboratory, clinical, healthcare, or other regulated environment (CAP/CLIA, CLIA, HIPAA, or similar), including familiarity with validation and change-control requirements.

DECISON MAKING

Decisions this role makes alone

• Implementation-level decisions within an assigned scope of work: code structure, class and method design, algorithm and data-structure selection, naming, and refactoring of existing code within an established pattern. Selection and application of design patterns consistent with existing system conventions.
• Local database schema changes within an owned component. Test strategy and coverage for their own work. Day-today use of AI-assisted development tooling, including how to scope and prompt a task, and whether to accept, revise, or discard AI-generated output.
• The developer decides independently when generated code is not fit to ship. Prioritization and sequencing of their own assigned tasks within a sprint or committed timeline. Troubleshooting approach and diagnostic path when investigating a defect.
• When to raise a question, flag a risk, or request review from a peer or lead. Whether their own work is ready for code review or release candidate status.

Decisions this role makes under guidance

• Architectural decisions affecting more than one component or service, including introduction of new patterns, messaging topologies, or significant changes to system boundaries.
• Adoption of new libraries, frameworks, third-party services, or development tools not already in use on the team. Changes to shared infrastructure, CI/CD pipelines, or deployment configuration.
• Database schema changes that affect shared data, integrations, or historical laboratory records. Data migration approach and rollback planning. Scope negotiation and effort estimation for new features, including trade-offs between delivery timeline and technical approach.
• Decisions to defer or accept technical debt. Changes to user-facing workflows used by laboratory staff, including UI/UX direction and any change that alters how lab personnel perform a validated process.
• Expansion of AI-assisted tooling into new areas of the workflow, and standards governing its use on the team.

Decisions this role escalates

• Any change that may affect the integrity, accuracy, or traceability of clinical or consumer genetic data, or that touches a validated laboratory system or process subject to CAP/CLIA requirements.
• Suspected or confirmed security incidents, data exposure, unauthorized access, or handling of protected health information outside established procedures.
• Production incidents that halt or materially degrade laboratory operations, sample processing, or result reporting.
• Discovery of defects with potential impact on previously released results, reports, or data delivered to customers or clinical partners.
• Commitments to external parties, vendors, or customers, including delivery dates, contract terms, or service expectations.
• Requests to bypass established change-control, validation, code review, or release procedures, regardless of source or urgency.
• Regulatory, compliance, or legal questions, and any decision materially affecting budget, headcount, vendor selection, or project scope beyond the assigned work.