At DNAstack, our mission is to power precision medicine by building software that breaks down barriers to responsible biomedical data sharing, discovery, and analysis. We build cutting-edge software and industry standards to help researchers and clinicians analyze sequencing data and make faster, more accurate diagnoses. Our platform supports national and international networks tackling rare disease, cancer, infectious disease, and more. We’re a nimble, cross-functional team of scientists, engineers, designers, and product thinkers working at the intersection of genomics, software, and cloud technologies. The Platform Engineering Lead sets the direction for the team behind the infrastructure our engineers and customers depend on: GCP and AWS environments, Kubernetes, Terraform and Helm, CI/CD, security and the tooling around them. You lead the team and stay hands-on: you review code, shape architecture and step in on implementation where it matters. You will own four things: the growth of the people on the team, the team's priorities, the platform roadmap (planned with Product), and the platform's technical direction. Direction first. Technical credibility. You make the cost and risk of every choice visible to the team, to Product and to leadership, including the case for more investment when the work calls for it. Manage and grow the team through 1:1s, career conversations, growth plans, performance reviews and hiring. Own the team's rituals, including planning, retrospectives and incident reviews. Coach senior engineers and build a culture of individual empowerment, accountability, and collaboration. Triage requests from Product, Program Management and customers against it, and decide what the team defers or stops. Plan the platform roadmap with Product, so reliability, security,



tooling and customer environments are planned alongside product features. Report progress, risks and spend to the VP of Product Development and the leadership team. Set technical direction Set the direction of the platform and decide how technical decisions are made, documented and revisited. Guide architecture and stay hands-on through design reviews, code reviews and implementation. Settle technical trade-offs across teams and review major changes, including new customer deployments, for cost and risk. Define how we measure delivery, including deployment frequency, lead time, change failure rate, time to restore and build and test durations, and act on what the numbers show. Set direction for the path from commit to production: fast, reliable CI, preview environments with representative genomic test data, and safe, routine deployments with progressive rollouts and automated rollback. Use AI and deterministic automation to give a small team leverage, with guardrails for agent access and KPIs that track time saved. Own the platform for AI-assisted development: tooling, access, licensing and budget. Own the infrastructure budget across GCP, AWS and related tooling: forecast, track against plan and explain variances. Build cost visibility per environment, customer and product. Set cost targets and manage vendor and licensing relationships, with renewals planned well ahead. Own platform reliability:



service level objectives for customer-facing environments, a clear rotation for on-call, deployments, alerts and support requests, incident response and blameless reviews. You own the technical side: access, secrets, CI and audit evidence. 8+ years in DevOps, site reliability or platform engineering, including 3+ years managing engineers. ~ Experience setting technical direction and priorities for a platform or infrastructure team, and managing senior engineers. ~ Production experience with Kubernetes, Terraform and a CI system on GCP or AWS, and the hands-on skill to review and contribute to that work. ~ Experience with SOC 2 or a comparable control framework, and comfort working with health or genomic data where access rules are strict and audited. ~ Strong communication, including explaining technical trade-offs and costs to non-technical leaders, and ease working across global time zones. Experience using AI and automation to multiply output, including guardrails for agent access. Experience building cost allocation or showback models, or internal developer platforms. Familiarity with Java services built on Spring Boot, GA4GH standards or WDL workflow engines. Your work will directly influence tools used by national and international genomics networks. Shape a core function of the company from a small, senior team into a scalable, sustainable group. Enjoy a flexible, remote-friendly team culture along with a competitive salary, advantages, and employee stock option program. This role offers the flexibility of remote work, with the option to work in person from our Toronto office. Remote friendly, with flexible hours and the opportunity to work on-site at our Toronto office

📌 Platform Engineering Lead (Toronto)
🏢 DNAstack
📍 Toronto