Senior Platform Engineer - AI
$156.8k - $229.7kGFiber
At GFiber, we believe that great internet has the power to drive innovation, strengthen communities, enable the impossible, and do all the everyday things that make all of our world go round. And the job of creating better internet is never done - so we're growing! Our team is committed to building a place where people who want to make a difference can grow their careers and find their spot to belong.
GFiber is an Alphabet company that brings Google Fiber and Google Fiber Webpass internet services to homes and businesses across the United States. Our teams are expanding as we connect more cities and people to exceptional internet. The application window will be open until at least June 1, 2026 . This opportunity will remain online based on business needs which may be before or after the specified date. This role is not eligible for immigration sponsorship. Role Description GFiber is currently at a transformative crossroads. As we ramp up investments in AI-driven product features, the Platform Engineering team is the engine room for this evolution. We are modernizing our foundational systems to support a new generation of AI initiatives, focusing on:- Agentic Platforms : Building the frameworks for autonomous AI agents.
- AI Observability & Security : Implementing guardrails and monitoring specifically for LLMs.
- AI-Centric DevOps : Developing specialized CI/CD pipelines and automated testing frameworks tailored for AI Agents and machine learning workflows.
- Architect and build the Internal AI Developer Platform (IDP), abstracting complex GCP AI services (Vertex AI, Agent Engine, Model Garden) into self-service, "paved-path" APIs, SDKs, or Terraform modules that product engineering teams can easily consume without needing deep AI infrastructure expertise
- Design and Build enterprise Model Gateways. Must have experience building unified routing layers that manage rate-limiting, load balancing, failovers, and unified telemetry, allowing the platform team to swap underlying models seamlessly without breaking downstream product applications.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines grounded in internal client policies and technical documentation.
- MLOps & Deployment: Oversee the deployment of microservices using GKE (Google Kubernetes Engine), Cloud SQL, and Cloud Build, ensuring scalable and reliable AI performance.
- Bachelor's degree in Computer Science, a related field, or equivalent practical experience
- 8 years of experience in setting up SDLC, CI/CD pipelines, automation, troubleshooting, launching and supporting enterprise applications as an individual contributor and in a Lead capacity.
- 5 years of experience as senior platform engineer, with recent years dedicated to architecting and scaling enterprise AI infrastructure. Demonstrated expertise in building multi-agent systems, workflow automation, and implementing emerging integration frameworks (such as A2A and MCP).
- 5 years of hands-on experience with public cloud and Infrastructure as Code (IAC).
- Experience with Python, Java and GCP infrastructure tools (GKE, CloudRun, CloudFunctions, GCS, etc) and experience with cloud infrastructure management and automation technologies (Terraform, Ansible etc)
- Experience optimizing applications, both stand-alone and in distributed systems to maximize performance
- Hands-on experience with Google Cloud Platform (GCP).
- Experience with multi-cloud environments and other cloud providers (AWS, Azure, etc.)
- Problem-solving and analytical skills
- Communication and teamwork skills
It's important to us to create an accessible, inclusive workplace for everyone. If you have a need that requires accommodation, please let us know by completing our accommodations for applicants form. Our candidate accommodations team will then connect with you to confidentially discuss your options.
Vacancy posted 4 days ago
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