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Easy Apply
This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.
At Viral Nation, we specialize in building social-first ecosystems for brands to connect with the modern consumer journey. Our integrated solutions align strategy, talent, media, and technology with culturally relevant creativity to scale the world’s fastest-growing digital brands. Viral Nation offers a fluid, creative, and growth-oriented environment that will support your ambitions to apply your talents in an open, collaborative, and fast-paced culture. Our ability to stay at the forefront of the industry has fuelled our success and will guide us in paving the path forward. We’re driven to push boundaries and think beyond today to deliver strategies, and we’re just getting started.
While we continuously exceed our goals, we need your help – our success is only as great as our people. Strong performance leads to high expectations, and we must keep raising the bar!
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.
What You'll Do Here:- 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.
Compensation Philosophy:
At Viral Nation, compensation is structured, performance-led, and market-aligned. Pay decisions are intentional, based on role requirements, performance, and market alignment by country, and are set to maintain internal pay equity across comparable roles and levels.
Compensation progression is tied to demonstrated performance, expanded scope, and sustained contribution over time, not tenure alone. Employee compensation is reviewed regularly through formal performance reviews and check-ins to ensure alignment with role expectations and impact.
AI in Recruitment:
Viral Nation does not use AI-enabled tools to screen, assess, rank, or select candidates in our recruitment process. Our hiring teams make all hiring decisions.
DEI Commitment:
Viral Nation is committed to diversity, equity and inclusion in our agency. Viral Nation welcomes applications from people with visible and non-visible disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruiting and selection process.
Top Skills
Docker
Github Actions
Gke
Google Adk
Google Cloud Platform
Google Rag Engine
Model Context Protocol
Python
Vertex Ai Pipelines
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