Agent AI Architect

We are seeking a highly skilled Agentic AI Architect to lead the design and development of sophisticated AI agent systems using Google Cloud Platform's Vertex AI suite. This hands-on role requires deep expertise in building autonomous AI systems that can reason, plan, and execute complex tasks using large language models and advanced orchestration frameworks.

Required Technical Skills

• Core AI & ML: Extensive experience with Google Vertex AI suite (Gemini Pro/Ultra, PaLM 2, Codey, Imagen)
• Deep understanding of agentic AI patterns: ReAct, Chain-of-Thought, Tree of Thoughts, and multi-agent workflows Proficiency with LangChain, LangGraph, and agent orchestration frameworks
• Experience with Model Context Protocol (MCP) for agent-to-agent communication
• Knowledge of prompt engineering, fine-tuning, and model optimization techniques
• Google Cloud Platform: Vertex AI Workbench, Pipelines, and Model Registry Cloud Functions, Cloud Run, and App Engine for serverless deployments BigQuery for data processing and analytics Cloud Storage, Firestore, and Cloud SQL for data management Pub/Sub for event-driven architectures
• Cloud Logging, Monitoring, and Error Reporting Programming & Development: Advanced Python programming (5+ years) Experience with FastAPI, Flask, or Django for API development Containerization with Docker and Kubernetes (GKE) Infrastructure as Code (Terraform, Cloud Deployment Manager) Version control with Git and CI/CD pipelines (Cloud Build, GitHub Actions)
• Data & Vector Systems: Vector databases (Vertex AI Matching Engine, Pinecone, Weaviate, or Chroma) Embedding models and similarity search optimization
• Knowledge graph construction and reasoning
• Structured and unstructured data processing

Preferred Qualifications

• Experience with additional agent frameworks (AutoGen, CrewAI, Semantic Kernel)
• Knowledge of graph databases (Neo4j, Amazon Neptune)
• Familiarity with other cloud platforms (AWS Bedrock, Azure OpenAI)
• Understanding of function calling, tool use, and external API integration
• Experience with streaming and real-time AI applications
• Background in distributed systems and microservices architecture
• Knowledge of AI safety, alignment, and responsible AI practices.
• Experience on Agile methodologies
• Solid understanding of core and modern technologies around Cloud, APIs, Web-services

Experience Requirements

• 10+ years in software engineering with 3+ years focused on AI/ML systems
• 2+ years hands-on experience with production LLM applications
• Demonstrated experience building and deploying agentic AI systems
• Track record of architecting scalable cloud-native applications
• Experience leading technical teams and mentoring junior developers
• Experience working in automotive

Education

• Bachelor's or Master's degree in Computer Science, AI/ML, or related technical field
• Preferred Relevant certifications (Google Cloud Professional ML Engineer, AI/ML specializations) preferred