About the role
About Tapestry
Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world’s most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.
Originally born at X, Alphabet’s moonshot factory, Tapestry brings together experts in energy, AI, software engineering, and products to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.
This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.
Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.
About the Role
We are seeking a Senior Backend Software Engineer to join our Infrastructure and Developer Productivity team.
Our systems must process massive amounts of power-grid data, run heavy scientific simulations, and support emerging AI workflows. You will treat our internal infrastructure as a product. Building reliable, self-service tools for our developers, automating our delivery pipelines, and creating secure environments where engineers and automated agents can build and test software quickly and safely.
How You Will Make 10X Impact
* Core Cloud & Compute Platform: Architect and operate scalable, multi-tenant Kubernetes clusters on Google Cloud Platform (GCP). Ensure efficient compute scheduling and autoscaling across mixed hardware workloads (CPUs, GPUs, and TPUs) supporting simulation and machine learning models. Design resilient networking, IAM boundaries, and secure multi-project cloud environments. * Developer Velocity & CI/CD: Design fast, hermetic, and automated build, test, and release pipelines that reduce cycle times for product engineers. Provide reliable, on-demand testing environments so teams can validate changes safely before production. Build automated deployment and rollback mechanisms with clear canary verification. * Infrastructure as Code & Security: Drive declarative, reproducible cloud infrastructure using modern Infrastructure-as-Code (such as Terraform). Implement automated policy checks, secret management, and container vulnerability scanning into standard deployment workflows. * AI Tooling & Execution Sandboxes: Design secure, isolated sandbox environments that allow automated AI tools and agents to safely run tests and inspect code. Identify high-leverage opportunities to automate repetitive developer workflows using modern AI tools. * Technical Co-Leadership & Mentorship: Partner with the team to split architectural ownership, guide system designs, and run engineering design reviews. Mentor mid-level and senior engineers (L4/L5), raising the technical bar for code reviews, testing, and system design. * Reliability & Observability: Define team-wide standards for metrics, logs, and distributed tracing to ensure high visibility into production health. Partner with data and ML teams to establish SLAs/SLOs, lead disaster recovery exercises, and run blameless post-mortems.
What You Should Have
* Technical Breadth & Depth: 8+ years of production experience in Infrastructure, Site Reliability Engineering, DevOps, or Developer Productivity/Platform Engineering. * Modern Cloud & Orchestration: Advanced production-grade expertise with Kubernetes (GKE), container networking, and multi-tenant cloud architectures (Google Cloud Platform preferred). * Infrastructure as Code (IaC): Deep architectural experience with modern declarative tools (Terraform, Pulumi, or similar) managing complex multi-environment cloud footprints. * CI/CD & Developer Experience Primitives: Proven track record building large-scale, automated build/test/release pipelines (e.g., Tekton, GitHub Actions, Argo Workflows, Bazel) designed around self-service internal developer platforms. * Platform-as-a-Product Mindset: Demonstrated ability to interview internal engineering stakeholders, quantify developer friction points, and deliver platforms that measurably increase overall deployment frequency and reduce MTTR.
Preferred Qualifications
* AI & Agentic Workloads: Practical experience designing infrastructure, sandboxes, and execution runtimes specifically geared toward AI agents, LLM evaluations, or high-performance GPU orchestration. * Data Platform Adjacency: Hands-on architectural exposure to supporting large-scale data platforms (e.g., BigQuery, Spark, Kafka, Ray) or complex distributed simulation environments. * Alphabet Ecosystem: Working knowledge of Google-internal infrastructure primitives (Borg, Monarch, Spanner, Piper/Blaze) or experience operationalizing an X moonshot into an independent production environment. * Tier-1 Tech Platform Experience: Background engineering high-throughput platform tooling or developer infrastructure at companies operating at high engineering scale (e.g., Netflix, Snowflake, LinkedIn, Datadog).
Our Values
* Take charge: We take initiative and own outcomes that move the mission forward. * Transform with purpose: We build solutions that solve real problems and create meaningful impact. * Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually. * Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn. * Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.
What we offer
A culture that supports growth, ownership, and meaningful impact, along with:
* Competitive salary and equity * Medical, dental, and vision coverage * Generous PTO and flexible hybrid work model * 401(k) with employer contribution * Professional development * The ability to work on important real-world problems within an Alphabet-backed environment
The US base salary range for this full-time position is $174,000 - $255,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, or benefits.