AI Integration Engineer, AI/ML

Viral Nation is seeking an AI Integration Engineer, AI/ML to serve as the primary technical engine translating high-level architectural visions into production-ready reality. Reporting directly to the Principal Architect, AI/ML and VP of Engineering, you will be responsible for the hands-on development, integration, and deployment of AI/ML models and agentic workflows within our GCP ecosystem.

• You will transform the Principal Architect’s reference architectures into scalable, deployable code using Python, GKE, and Cloud Run.
• Your primary focus involves building out agentic ecosystems using Google ADK (Agent Development Kit) and Model Context Protocol (MCP), specifically focusing on the Agent-to-Agent (A2A) orchestration patterns defined by the Architect.
• You will apply advanced prompt engineering and context engineering techniques to optimize LLM performance, ensuring agents maintain state and accuracy over long interactions.
• You will develop and tune high-fidelity RAG pipelines using the Google RAG Engine and Agent Engine to ensure agents have the precise context required for influencer marketing workflows.
• The role requires applying machine learning techniques to our massive datasets to implement automated anomaly detection, forecasting, and trend analysis.
• You will perform advanced data science and analysis by generating and querying high-dimensional video and text embeddings to extract insights from social media content.
• You will integrate Gemini and Model Garden LLMs into production applications while managing the technical nuances of token limits and context window optimization.
• Partnering with the Architect, you will implement MLOps practices that track agent performance, cost-efficiency, and ethical AI safeguards within the GCP IAM framework.

• Advanced proficiency in Python is required for AI/ML backend development, data analysis, and API construction.
• You must possess a deep understanding of prompt engineering strategies (Chain-of-Thought, ReAct) and context engineering to maximize model reasoning capabilities.
• The position demands deep hands-on experience with Google ADK, MCP, Vertex AI Pipelines, and the Google RAG Engine.
• You should have practical experience applying classical ML algorithms for regression, forecasting, and anomaly detection on large-scale datasets.
• The role requires a strong understanding of vector databases and the manipulation of video/text embeddings for semantic search and classification.
• Deep experience with utilizing GitHub Actions to support the SDLC workflows and CI/CD standards established by the Principal Architect.

• Experience utilizing Snowflake Cortex Analyst, Cortex Search, and Snowflake Intelligence ecosystem.
• Proficiency in Node.js for full-stack integration layer and tool development is highly regarded.
• Prior experience in the digital marketing or influencer marketing space is a significant advantage.
• Experience with containerization and orchestration using Docker and GKE will help scale our autonomous systems.