We are seeking a skilled AI Infrastructure Architect to design and implement custom Artificial Intelligence (AI) infrastructure and hardware solutions. This role focuses on optimizing performance, power consumption, cost, and scalability of computational stacks.

You will provide expert advice on AI infrastructure technologies, including vendor evaluation, selection, and full-stack integration. The position requires a minimum of 3 years of experience in relevant areas.

Develop and deploy sophisticated AI agents using platforms like Google Vertex AI Agent Builder, Gemini Enterprise Agentic Platform services, and Dialogflow CX.

Integrate LLM-powered reasoning pipelines, incorporating Gemini, tool use patterns, RAG, and memory patterns.

Build and maintain robust serverless orchestration solutions with Cloud Run, Cloud Functions, and Pub/Sub.

Implement efficient APIs and microservices using Python and Node.js, and connect agents with enterprise systems.

Collaborate effectively with ML engineers and product managers in Agile sprints, participate in code reviews, and contribute to technical documentation.

Possess 3 to 5 years of professional software development experience, with hands-on expertise in Google Cloud Platform services such as Vertex AI, Gemini Enterprise Agentic Platform, Cloud Run, Google Cloud Storage, Pub/Sub, and BigQuery.

Demonstrate working knowledge of LLM APIs and prompt engineering fundamentals. Exhibit proficiency in Python and Node.js.

Familiarity with agentic frameworks like ADK, LangChain, LangGraph, or CrewAI is beneficial. Experience with RESTful API design, event-driven architectures, and CI/CD pipelines is expected.

A basic understanding of IAM, VPC, and GCP security best practices is required, alongside strong problem-solving abilities and a growth mindset.