AI Platform Engineer

We are seeking anAI Platform Engineer to help design and build Python SDKs, ADKs (agent development kits), and platform frameworks that enable teams to deliver GenAI and agentic automation at scale. You will contribute to developer-first tooling, reusable components, and production-grade standards for deploying AI agents on cloud infrastructure.

Responsibilities

• Develop SDKs, ADKs, and platform libraries in Python
• Contribute to core frameworks, abstractions, and tooling for AI agents, copilots, and GenAI applications
• Implement developer-facing APIs and integrations with LLMs and enterprise systems following the defined SDK architecture
• Build reusable AI components, RAG building blocks, and prompt engineering primitives
• Implement retrieval patterns spanning vector search and graph-native data (Spanner Graph, Neo4j) for relationship-aware agent context
• Prepare documentation, samples, and reference implementations for SDK/ADK adopters
• Collaborate with Cloud/DevOps teams to package, distribute, and deploy platform components on GCP, using Terraform for infrastructure-as-code
• Follow versioning, testing, benchmarking, and quality standards for releases
• Implement guardrails and safety controls for production LLM/agent traffic

Requirements

• 3+ years of Python experience building libraries, SDKs, or frameworks
• 1+ years of hands-on agentic AI experience building and orchestrating AI agents
• Experience contributing to production-grade SDKs or platform components
• Ability to participate in architecture discussions and support less experienced engineers
• Strong Python skills with asyncio, type hints, dataclasses, Pydantic, and pytest
• Good API engineering skills with FastAPI and async-first REST design
• Hands-on cloud AI experience with Google Vertex AI for serving and orchestration
• Infrastructure-as-code experience with Terraform for deployment automation
• CI/CD and release engineering skills with Jenkins, Git, semantic versioning, packaging, and Docker
• Observability skills with structured logging, distributed tracing, and telemetry tooling
• Good problem-solving skills with attention to developer experience and API design
• Clear communication skills and ability to collaborate across DevOps and engineering teams
• Minimum English language level of B1+

Nice to have

• Google Cloud Platform experience with services for AI workloads
• Google Agent Development Kit experience for building agent frameworks
• MLOps exposure with Kubeflow and production ML/LLM delivery practices
• Kubernetes experience for scalable deployment and platform operations
• Prompt Engineering experience for reusable templates, evaluations, and agent behaviors