Skill Set Needed
Be a trusted technical advisor to customers and solve complex machine learning challenges. Coach customers on the practical challenges in machine learning systems feature extraction, feature definition, data validation, monitoring, and management of features and models. Architect and implement multi-step Agentic AI workflows using ADK, Agent Engine, LangChain, Vertex AI, and AgentSpace. Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production. JD
As a Staff Solutions Architect, you will serve as a trusted technical advisor to our strategic customers, helping them solve their most complex machine learning and AI challenges. You will bridge the gap between cutting-edge AI research and production-grade enterprise deployments—coaching client teams through the practical realities of feature engineering, model governance, and multi-step agentic workflows. Working closely with customers, partners, and Google Product teams, you will architect, implement, and bring tailored AI solutions into production. Key Responsibilities Technical Advisory & Customer Coaching Serve as the primary technical partner for customer engineering leadership, translating business goals into scalable AI/ML architectures. Guide and coach customer teams through real-world MLOps and system-design challenges
Feature Engineering
Feature extraction, definition, and transformation pipelines. Data Quality
Data validation, schema drift, and automated data checks. System Operations
Continuous monitoring, lineage, and management of features and models in production. Agentic AI & Systems Architecture Architect, prototype, and implement enterprise-grade, multi-step Agentic AI workflows. Leverage state-of-the-art frameworks and platforms, including Agent Development Kits (ADK), Agent Engine, LangChain, Vertex AI, and AgentSpace. Design resilient systems with human-in-the-loop validation, tool orchestration, and multi-agent coordination. Cross-Functional Collaboration & Delivery Collaborate directly with Google Product and Engineering teams to share field feedback, influence product roadmaps, and resolve complex technical blockers. Partner with external implementation partners and client engineering teams to ensure smooth end-to-end delivery into production environments. Develop reusable architectural blueprints, whitepapers, and code samples to elevate team and community capabilities. Required Qualification