Principal Software Engineer , NY Software Engineering

At the New York Genome Center (NYGC), the Principal Software Engineer is primarily an individual contributor who sets technical direction and leads the design and delivery of high-impact software across interconnected products and systems. The role applies engineering judgment to challenges with unclear or not-yet-defined requirements that span departments; builds and evolves reliable, secure, maintainable solutions; and remains hands‑on in architecture, implementation, and production operations.

Working across scientific, clinical, and operational teams, the Principal Software Engineer establishes durable engineering practices, guides technical decisions, and mentors engineers while partnering with engineering leaders on technical approach and delivery priorities. Supervisory responsibility for one or two direct reports may be assigned based on organizational needs and the individual's demonstrated experience and skill set.

• 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,…