Architect AI Solutions: Build and deploy production-grade AI features, including RAG (Retrieval-Augmented Generation) pipelines, LLM orchestrations, and Agentic workflows using Vertex AI.
Develop Core Logic: Write clean, maintainable, and highly efficient code in Python to support AI model integration and data-intensive applications.
Optimize Model Performance: Fine-tune models for specific business logic and optimize LLM prompts to ensure accuracy, relevance, and safety for enterprise use cases.
Engineer Data Sources: Optimize and manage data sources and vector databases to ensure high-quality retrieval for context-aware AI systems.
Collaborate Globally: Work closely with US-based product owners and European delivery teams, requiring a proactive communication style and flexibility for early-morning syncs.
Ensure Quality: Champion best practices in AI observability, evaluation frameworks, and automated testing to ensure the reliability of enterprise-level deployments.
Consult with Clients: Partner with clients to develop new AI concepts and enhancements, translating business goals into technical AI roadmaps.

4+ years of professional experience in software engineering, with a significant focus on AI/ML implementation.
Mastery of the Vertex AI ecosystem and proven experience integrating LLMs into production-grade applications.
Mastery of the Python ecosystem, specifically libraries used for AI development and data manipulation.
Hands-on experience with Google Cloud Platform services, specifically Vertex AI, BigQuery, and Cloud Functions.
Proficiency with Docker and CI/CD pipelines as they apply to MLOps workflows.
Fluent English skills with the ability to discuss technical trade-offs clearly with both peers and stakeholders.

Senior AI Engineer

Key skills