Principal Software Engineer

Essential Duties and Responsibilities

• Set technical direction and architecture across the software product suite, services, data systems, and integrations; align design choices with organizational needs, system constraints, and long-term maintainability.
• Lead high-impact and ambiguous cross-functional projects from discovery through release and production support; set the technical execution approach and manage architecture, risk, dependencies, and delivery tradeoffs.
• Remain hands-on in designing, developing, reviewing, testing, deploying, documenting, and maintaining production software, APIs, data-processing services, scientific workflows, and operational tooling.
• Lead the design and evolution of interconnected operational systems that support genomic testing from sample accessioning through laboratory and sequencing workflows, computational analysis, clinical reporting, and secure genomic-data exchange; improve the integrations, reliability, and observability that enable those systems to operate at scale.
• Work with scientific, clinical, and operational stakeholders to determine needs and establish specifications where requirements are unclear or not yet defined; translate them into scalable technical approaches and clear implementation plans; explain tradeoffs and build agreement across teams and stakeholders.
• Partner with lab supervisors, clinical directors, computational biologists, Research Computing, and focused working groups to deliver dependable services and improve cross-system workflows.
• Establish and advance shared engineering practices for architecture, version control, code review, automated testing, release management, documentation, observability, data protection, and secure handling of sensitive information across related products and systems.
• Guide modernization and technical-debt work; identify opportunities to simplify systems, improve reliability and performance, and reduce operational burden through incremental, supportable changes.
• Diagnose system-wide quality, performance, capacity, integration, and production challenges; bring the right expertise together, evaluate options, and drive root-cause solutions across system boundaries.
• Mentor and coach engineers through design discussions, code reviews, and knowledge sharing; strengthen technical capability and shared practices, and support reliable delivery. When direct reports are assigned, provide regular supervision, coaching, and performance feedback.
• Communicate technical options, decisions, dependencies, risks, and progress to the Software Engineering team, stakeholders, and organizational leaders; provide evidence-based recommendations that inform technical roadmaps and shape major cross-functional initiatives.
• Use approved AI-enabled tools, where appropriate, to support software development, testing, documentation, and troubleshooting. Validate outputs for accuracy, security, privacy, and compliance with NYGC policies before relying on them.
• Guide the technical evaluation and responsible adoption of AI tools and AI-enabled capabilities across related products and workflows, consistent with NYGC approval, security, privacy, and governance requirements. Establish practices for validation, security, privacy, compliance, reliability, and operational support.

Minimum Qualifications

• Bachelor’s degree in Computer Science with 12+ years of relevant software engineering experience, or a Master’s degree in Computer Science with 10+ years of relevant software engineering experience.
• Demonstrated success leading high-impact, cross-team software initiatives from problem definition and specification through delivery and ongoing production support.
• Demonstrated software architecture and engineering expertise across multiple related technical areas, including sound judgment in decisions that affect interconnected systems.
• Proficiency in one or more modern programming languages and object-oriented design, and a record of delivering extensible, well-tested, maintainable production software.
• Experience designing or integrating APIs, databases or other data systems, and production services or workflows.
• Demonstrated ability to improve engineering quality, reliability, security, and operational practices across a team or group of related systems.
• Strong written and verbal communication skills, including the ability to explain technical tradeoffs and influence decisions with scientific, technical, operational, and leadership stakeholders.
• Ability to work independently on broad technical problems, collaborate across functions, and develop expertise in new scientific and technical domains.

Preferred Qualifications

• Experience supporting scientific, clinical, bioinformatics, or other data-intensive software applications across multiple products or systems, including analysis workflows, data repositories, laboratory information systems, enterprise integrations, and large-scale data movement.
• Experience with cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS); infrastructure as code; CI/CD pipelines; containerized services such as Docker, Apptainer/Singularity, Kubernetes, or Cloud Run; workflow orchestration with tools such as Nextflow, Snakemake, Workflow Description Language (WDL) with Cromwell or similar engines, or Airflow; durable execution frameworks; cluster job schedulers such as Slurm, LSF, or Grid Engine, or cloud batch services; Python; PostgreSQL and other relational, document-store, graph, or analytical databases; GraphQL; FAIR (Findable, Accessible, Interoperable, Reusable) and AI-ready data, including Resource Description Framework (RDF); and event-driven architectures using tools such as Kafka or Pub/Sub.
• Experience with genomics, computational biology, clinical bioinformatics, sequencing operations, or high-throughput computing environments.
• Experience establishing and advancing security and privacy practices for sensitive or regulated data across multiple related systems, aligning those practices with applicable requirements such as the Health Insurance Portability and Accountability Act (HIPAA) and the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-171, and designing audit-ready processes and operational controls.
• Experience using AI-enabled development tools or integrating AI capabilities into software workflows, including evaluating output quality, applying data-classification requirements, and protecting against inappropriate disclosure of data.
• Experience evaluating or integrating AI tools or capabilities in production systems within established approval and governance processes, including validation, security, privacy, and operational support.

Competencies

• Technical and Professional Skills: Demonstrates strong judgment, integrity, discipline, and reliability; appropriately prioritizes work, manages expectations, and consistently delivers on commitments.
• Collaborative & Communicative: Builds strong relationships across functions; communicates clearly and thoughtfully; listens carefully; fosters collaboration and trust.
• Adaptable & Innovative: Embraces change, anticipates challenges, develops practical solutions, and continuously seeks opportunities to improve organizational effectiveness.