AI Engineer Development

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Applicants are considered for employment without attention to or discrimination against race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. All employment is decided on the basis of qualifications, merit and business need.

• Design and implement stateful, multi-agent workflows using Lang Graph and the Google Agent Development Kit.
• Develop generative AI applications that integrate enterprise data sources using Model Context Protocol (MCP) for secure LLM interaction.
• Architect and deploy AI services on Google Cloud Platform using Vertex AI, Cloud Run, and Cloud Functions.
• Build and maintain REST APIs in Python using frameworks such as FastAPI or Flask to expose AI capabilities.
• Develop data pipelines, embeddings, and retrieval layers using Big Query and vector databases.
• Implement Retrieval-Augmented Generation architectures and establish evaluation mechanisms to monitor response quality, accuracy, and performance.
• Optimize prompts, monitor model latency, and manage production workloads for reliability and cost control.
• Maintain version control using Git and contribute to CI/CD pipelines for automated deployment.
• Collaborate with product owners and platform teams while producing design documentation, runbooks, and production support during rollout.

Applicants are considered for employment without attention to or discrimination against race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. All employment is decided on the basis of qualifications, merit and business need.