This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr Director Software Engineer based in United States.
This is a senior technology leadership opportunity focused on building and scaling software platforms that support clinical genomic diagnostics.
You will lead a high-performing software engineering organization spanning bioinformatics, data platforms, workflow automation, and production systems.
The role combines strategic ownership with strong technical oversight, shaping architecture, engineering standards, roadmaps, and delivery priorities.
You will work closely with scientific, clinical, quality, operations, product, and executive stakeholders to translate complex requirements into reliable software solutions.
A key focus will be modernizing legacy platforms and transitioning research innovations into validated, production-ready workflows.
You will also champion responsible AI adoption, automation, observability, and engineering practices that improve quality, efficiency, and scalability.
This is an opportunity to influence technology strategy in a mission-driven, regulated environment where software directly supports advanced genomic diagnostics.
Accountabilities:
- Define and own the software engineering vision, technical roadmap, delivery priorities, operating model, resource plans, and engineering standards for a bioinformatics software engineering organization.
- Lead, mentor, hire, and develop software engineers, bioinformatics engineers, technical leads, and managers while fostering accountability, collaboration, technical excellence, and continuous improvement.
- Oversee the architecture, development, implementation, maintenance, and operational support of production-grade software platforms, bioinformatics workflows, data systems, and reporting solutions.
- Drive modernization initiatives involving legacy systems, workflow orchestration, automation, containerization, cloud and HPC computing, data integration, APIs, and scalable software architectures.
- Establish strong production operations practices, including monitoring, observability, incident response, escalation processes, root-cause analysis, post-release support, and reliability improvements.
- Partner with R&D, clinical laboratory, quality, operations, product, data, and executive stakeholders to translate scientific, clinical, and business priorities into actionable software roadmaps.
- Lead prioritization, scope definition, dependency management, resource planning, delivery governance, and executive communication across complex software initiatives.
- Guide research algorithms, analytical prototypes, scripts, and proof-of-concept tools through the transition into scalable, tested, validated, documented, and maintainable production workflows.
- Establish and enforce software development lifecycle standards covering requirements, architecture reviews, code reviews, automated testing, CI/CD, validation, documentation, release management, and change control.
- Ensure software practices meet applicable quality, regulatory, privacy, security, traceability, and audit-readiness expectations within clinical diagnostics and other regulated environments.
- Define and monitor engineering KPIs covering roadmap delivery, system reliability, software quality, technical debt, production incidents, team health, stakeholder satisfaction, and operational efficiency.
- Lead responsible adoption of AI-enabled engineering, workflow automation, documentation, decision-support, code assistance, issue triage, and operational capabilities, with appropriate governance and human oversight.
- Reduce technical debt and improve scalability, maintainability, performance, deployment efficiency, automation, documentation, and integration across critical platforms and workflows.
- Evaluate technology investments, build-versus-buy decisions, architecture patterns, and emerging technologies to ensure long-term alignment with organizational strategy.
- Communicate technical decisions, risks, tradeoffs, roadmap progress, and recommendations effectively to executive, technical, scientific, clinical, quality, and business audiences.
Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, Bioinformatics, Computational Biology, Genomics, Data Science, or another relevant technical or quantitative field.
- 12+ years of experience in software engineering, bioinformatics software development, clinical genomics technology, data platforms, or related computational technology disciplines.
- 7+ years of software engineering leadership experience, including people management, hiring, performance management, mentoring, organizational planning, and leadership of technical leads or managers.
- Demonstrated success defining engineering strategy, technical roadmaps, delivery priorities, resource plans, and operating models for complex software organizations or platforms.
- Proven experience leading production-grade software systems, bioinformatics workflows, data platforms, workflow automation, or reporting applications in clinical, healthcare, laboratory, or regulated environments.
- Strong expertise in software architecture, system design, APIs, data integration, database-backed applications, workflow orchestration, scalable computing, and modern software development practices.
- Experience establishing or improving engineering standards covering requirements management, code review, automated testing, CI/CD, validation, documentation, release management, incident management, and production support.
- Practical understanding of NGS data, clinical genomics workflows, bioinformatics pipelines, genomic data formats, variant analysis, laboratory interfaces, or diagnostic reporting systems.
- Experience transforming research prototypes, analytical methods, scripts, or proof-of-concept solutions into scalable, validated, documented, and maintainable production workflows.
- Experience operating within quality, regulatory, privacy, security, traceability, and audit-readiness frameworks relevant to clinical diagnostics, healthcare technology, laboratory operations, or regulated software.
- Strong technical fluency with Git-based development, automated testing, CI/CD, Linux, containers, workflow orchestration, cloud or HPC computing, databases, APIs, and monitoring or observability tools.
- Experience with technologies such as Nextflow, Docker, Kubernetes, cloud platforms, microservices, API-driven architectures, data lakes, data warehouses, and enterprise data integration is highly valuable.
- Familiarity with AI-enabled engineering tools, large language models, agentic AI, automation, decision-support systems, or AI-assisted operational workflows is preferred.
- Master’s degree or PhD in a relevant technical field is preferred.
- Experience with CAP/CLIA-regulated laboratory environments, molecular diagnostics, clinical genomics, variant interpretation, healthcare interoperability, or related domains is a strong advantage.
- Excellent written and verbal communication skills, with the ability to translate complex technical and scientific concepts for diverse stakeholders.
- Strong judgment, analytical thinking, problem-solving ability, and a practical approach to balancing quality, delivery, scalability, and business priorities.
- Demonstrated ability to collaborate effectively with scientists, engineers, clinical teams, laboratory personnel, quality professionals, and senior business leaders.
- Commitment to reproducibility, documentation, automation, maintainability, operational excellence, and high-quality engineering practices.
Benefits:
- Salary: Competitive compensation package based on experience, qualifications, and role requirements.
- Work arrangement: Fully remote position based in the United States.
- Opportunity to lead technology strategy for software platforms supporting clinical genomic diagnostics and scientific innovation.
- Senior-level ownership of engineering architecture, organizational development, modernization, and delivery strategy.
- Opportunity to work cross-functionally with software engineering, bioinformatics, R&D, clinical laboratory, quality, operations, product, and executive teams.
- Professional growth through leadership of experienced engineering teams and exposure to advanced genomics, regulated technology, cloud/HPC platforms, and AI-enabled engineering.
- Inclusive workplace committed to equal employment opportunity and a diverse workforce.
- Reasonable accommodations are available during the application process for qualified candidates.
- Remote work environment with responsibilities that may occasionally involve exposure to bloodborne or airborne pathogens or infectious materials.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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