GCP Agentic AI Developer

The Staff Agentic AI Engineer leads the design and delivery of enterprise-grade Generative AI and Agentic AI solutions on Google Cloud Platform (GCP), with a primary focus on Vertex AI. This role emphasizes production-ready AI systems, including Retrieval-Augmented Generation (RAG), grounding, embeddings, and autonomous agent architectures, while providing technical leadership and mentorship., Design, build, and deploy scalable Generative AI solutions on GCP using Vertex AI.

• Architect and implement RAG systems, including data ingestion, embeddings, vector search, and retrieval pipelines.
• Design grounding and embedding strategies to improve response accuracy and factuality.
• Develop Agentic AI and multi-agent systems for autonomous task execution.
• Integrate LLMs with external tools, services, and enterprise systems using structured interaction patterns (e.g., MCP).
• Build and manage cloud-native, containerized, and serverless AI workloads.
• Establish CI/CD pipelines and MLOps practices for AI/ML systems.
• Collaborate with product, business, and engineering stakeholders to translate requirements into AI solutions.
• Lead technical design reviews, investigations, PoCs, and solution proposals.
• Mentor engineers and promote best practices in AI engineering and Agile delivery.

Hands-on experience with Vertex AI and generative models (e.g., Gemini).

• Strong experience designing and delivering RAG architectures in production.
• Experience with vector databases, embeddings, and data grounding techniques.
• Proficiency in Python and at least one of: Java, C#, or Node.js.
• Experience with SQL and NoSQL databases (e.g., SQL Server, Cosmos DB, MongoDB).
• Experience with data pipelines and messaging systems (e.g., Dataflow, Dataproc, Pub/Sub, Kafka).
• Strong background in cloud-native architectures, Docker, Kubernetes, and microservices.
• Experience with DevOps and CI/CD for ML/MLOps.
• Strong communication, problem-solving, and technical leadership skills.

Preferred Qualifications

• Experience with Agentic AI frameworks (e.g., LangChain).
• Familiarity with Model Context Protocol (MCP) or similar LLM tool-integration approaches.
• Experience integrating AI solutions with CRM, ERP, eCommerce, or EMR/EHR systems.

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