Senior AI Platform Engineer - Agentic Systems & LLM Powered Platforms

This role is Remote in US!!

This role is not eligible for immigration sponsorship.

Email resume to Svitlana: [email protected] and mention where did you learn about this role.

Role Description

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. We are seeking a Senior AI Platform Engineer to lead the charge in designing and deploying our next-generation agentic systems and LLM-powered platforms. In this high-impact role, you will bridge the gap between cutting-edge AI Architecture and scalable Cloud Infrastructure. You’ll be architecting the entire ecosystem—utilizing advanced prompt engineering, LLM stack and DevOps practices to build AI Platform and optimize GFiber’s enterprise workflows.

In This Role, You'll

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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

Minimum Qualifications

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)

Nice To Have

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.)