GCP Agentic AI Developers

Role Name: GCP Agentic AI Developers - C2 - Onshore - GCP - C2 - 2
Work site: Nashville, US (Onsite)

Staff Agentic AI Engineer

Role Summary

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.

Key Responsibilities

- 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.

**Required Skills & Experience**

- 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**.