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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in software engineering, particularly in platform development and architecture, with a strong focus on AI integration and cloud infrastructure management. Proven ability to lead cross-functional initiatives, mentor engineers, and drive performance improvements in complex systems.
Highest-signal resume keywords
Software Engineering LeadershipInfrastructure As CodeKubernetes ExpertiseAI-Assisted DevelopmentCloud Cost Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonLinux InternalsNetworkingVirtualizationKubernetesSoftware ArchitectureAI/ML IntegrationWorkflow AutomationData ProcessingPerformance Tuning
Soft Skills
MentoringCollaborationJudgmentProblem-SolvingCommunication
Tools & Technologies
AzureGCPCI/CD ToolsCloud InfrastructureDistributed SystemsScientific Python FrameworksWorkflow OrchestrationMulti-Cloud OperationsOpen Lakehouse TechnologiesApache Iceberg
Industry Keywords
Life-Sciences SoftwareNGS PipelinesML OpsDeep LearningCloud MigrationsFinOps PracticesWorkload Cost AttributionBiological DataComputational BiologyData Science Technology Stack
Tech Stack
Tools & technologiesApacheAzureCloudDistributed SystemsGoogle Cloud PlatformKubernetesLinuxPython
About the role
Key responsibilities & impact- Shape Platform’s technical vision and roadmap with engineering and R&D leaders
- Treat Platform and Data as Products and translate shared domain-team needs into reusable platform solutions
- Design and ship scalable platform systems through architecture reviews, rapid prototypes and pragmatic technology choices
- Drive business-critical initiatives, resolve tradeoffs, sequence incremental deliverables and delegate execution
- Support platform users, troubleshoot complex system issues and improve reliability and capacity
- Champion AI adoption across Freenome by pairing with domain experts and tailoring guidance and tools
- Use AI for platform enhancements and build platforms for secure, cost-effective agentic workflows and LLM-powered applications
- Increase cloud-cost visibility and drive initiatives to reduce waste while protecting performance, reliability and scientific productivity
- Grow engineers through pairing, design review, delegation and feedback while reinforcing a high-performing culture
Requirements
What you’ll need- 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
- 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, including 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, including clean code, design documents, ADRs, constructive reviews and collaborative technical decisions
- Track record of helping engineers or domain experts grow and become more independent
- Experience partnering with specialist teams such as data science, AI/ML, computational biology or related fields
- Hands-on AI-assisted development and a record of building reusable tools or workflow automation
- Nice-to-have experience or interest in 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 Apache Iceberg; FinOps practices, workload cost attribution and measurable cloud savings
Benefits
Comp & perks- Equity
- Cash bonuses
- Full range of medical benefits
- Full range of financial benefits
- Other benefits
- Occasional travel to headquarters 2-3 times a year