Senior Staff Software Engineer (Platform Engineering) - Freenome

About this opportunity:

At Freenome, we are seeking a Senior Staff Software Engineer to grow our Platform team. Join a stellar group of engineers who serve our mission to save lives with early cancer detection as we develop and commercialize new blood test products. In this role, you’ll bring compute platform expertise to shape technical direction and mentor others, while staying hands-on and close to design, code, and operations.

Platform Engineering’s goal at Freenome is to multiply the productivity of domain experts. We build shared cloud services spanning a governed data lakehouse, batch and distributed compute, and self-service environments for research and analytics, championing developer effectiveness beyond engineering. We combine white-glove support with dedicated partnerships, bringing expert consulting and hands-on engineering to help specialist teams solve complex technical problems and meet critical business milestones.

This role reports to our Director of Engineering, Platform. This is a remote position within the US, with occasional travel to our headquarters in Brisbane, CA, 2-3 times a year.

What you’ll do:

• Shape Platform’s technical vision and roadmap, working with engineering and R&D leaders to align platform priorities with company goals.
• Treat Platform and Data as Products, building trust with leads and SMEs from domain teams, and translating shared needs into reusable platform solutions.
• Design and ship scalable platform systems, evolving the architecture through reviews, rapid prototypes, and pragmatic technology choices.
• Drive business-critical initiatives, resolving tradeoffs, sequencing work into incremental deliverables and delegating to scale execution.
• Support platform users to unblock critical work, troubleshoot complex system issues, and turn recurring issues into lasting reliability and capacity improvements.
• Champion AI adoption across Freenome, pairing with domain experts and tailoring guidance and tools to varied technical backgrounds.
• Expand our team’s impact by using AI for platform enhancements, and by building platforms for AI that empower Freenome users to create and deploy secure, cost-effective agentic workflows and LLM-powered applications.
• Increase visibility of cloud costs, recommend and drive initiatives to reduce waste while protecting performance, reliability, and scientific productivity.
• Grow other engineers through pairing, design review, delegation and feedback, while modeling Freenome’s values and reinforcing a high-performing culture.

Must haves:

• 12+ years of relevant software engineering experience or equivalent, preferably in platform teams, delivering complex systems from design to production.
• 3+ years guiding complex initiatives end-to-end across teams: aligning stakeholders, communicating tradeoffs clearly, and enabling delivery without formal authority.
• 3+ years building and operating production platforms using 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 and virtualization, with hands-on troubleshooting and performance tuning at system level.
• Solid Kubernetes expertise, with experience owning one or more advanced capabilities such as controllers, operators and 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.
• Software architecture leadership: you ship clean code, write clear design docs and ADRs, and guide constructive reviews and collaborative technical decisions.
• You are a force multiplier who enjoys helping engineers or domain experts grow, with a track record of making teams more capable and independent.
• Success partnering with one or more specialist teams - such as data science, AI/ML, computational biology or related fields - to improve their workflows.
• Hands-on AI-assisted development and a record of building reusable tools or workflow automation.

Nice to haves:

Experience, familiarity or a genuine interest in some of the following are preferred:

• Life-sciences software, NGS pipelines and biological data
• ML Ops, model development and deep learning
• Scientific Python frameworks and data-science technology stack
• Workflow orchestration and distributed compute frameworks on Kubernetes
• Cloud migrations, multi-cloud or multi-region operations
• Columnar processing, open lakehouse technologies, and modern table formats such as Apache Iceberg
• FinOps practices, workload cost attribution, and measurable cloud savings