3 hours ago
Base Salary
$188k - $270k/yr
Responsibilities
- Shape the Platform team’s technical vision and roadmap in partnership with engineering and R&D leaders.
- Build and evolve reusable cloud platform systems for governed data, batch and distributed compute, and self-service research and analytics environments.
- Lead business-critical cross-team initiatives, resolve tradeoffs, sequence deliverables, and delegate execution.
- Troubleshoot complex platform issues and convert recurring problems into reliability and capacity improvements.
- Champion AI adoption and build platforms that enable secure, cost-effective agentic workflows and LLM-powered applications.
- Improve cloud cost visibility and drive measurable waste-reduction initiatives while protecting performance and reliability.
- Mentor engineers through pairing, design reviews, delegation, and feedback.
Requirements
- 12+ years of relevant software engineering experience or equivalent, preferably delivering complex platform systems from design through production.
- 3+ years guiding complex initiatives end-to-end across teams without formal authority.
- 3+ years building and operating production platforms with Infrastructure as Code on a public cloud, preferably Azure or GCP.
- Proficiency in Python and at least one other high-level programming language.
- Deep knowledge of Linux internals, networking, virtualization, system-level troubleshooting, and performance tuning.
- Strong Kubernetes expertise, including ownership of advanced capabilities such as controllers, operators, CRDs, admission control, scheduling, autoscaling, service mesh, or multi-cluster networking.
- Sound judgment in distributed systems and platform design, including governance, capacity, reliability, cost, data processing, and storage.
- Experience providing software architecture leadership through clean code, design documents, ADRs, and constructive technical reviews.
- Ability to grow engineers and domain experts and make teams more capable and independent.
- Experience partnering with specialist teams such as data science, AI/ML, computational biology, or related fields.
- Hands-on AI-assisted development and experience building reusable tools or workflow automation.
- Preferred familiarity or interest in life-sciences software, NGS pipelines, biological data, ML Ops, model development, deep learning, scientific Python, data science technologies, workflow orchestration, distributed compute, cloud migrations, multi-cloud or multi-region operations, Apache Iceberg, and FinOps.
Benefits
- US base salary target range is $188,275-$270,375, with eligibility for equity, cash bonuses, and medical, financial, and other benefits.
- Remote position within the US with occasional travel to the Brisbane, California headquarters 2-3 times per year.
- Freenome is an equal-opportunity employer and provides legally required employment protections and notices.
Categories
About Freenome
Freenome develops blood-based cancer screening tests for healthcare providers, using a multiomics platform and machine learning to detect disease at early stages. The company’s initial product targets early colorectal cancer and advanced adenomas, with supporting software and data platforms used across its commercial, laboratory, and R&D operations. Founded in 2014 and headquartered in Brisbane, California, Freenome is privately held.