AI Solution Architect

Ready to help us transform healthcare? Bring your true colors to blue. The AI Solution Architect is responsible for designing and implementing specific architectural components and solutions for AI agents within the established Bluefield framework. This role works in close collaboration with Generative AI Engineers to convert architectural guidelines into practical, deployable systems, ensuring high technical quality at the project level. The ideal candidate will also act as a technical evangelist, sharing knowledge and showcasing the team's work through internal and external tech talks. Responsibilities ·       Design agentic workflows  — Architect multi-agent systems on Vertex AI Agent Builder, defining agent orchestration patterns (sequential, parallel, hierarchical), tool use strategies, function calling, and grounding configurations (Google Search, Vertex AI Search, custom data stores) ·       Build architecture blueprints  — Produce solution design documents, architecture decision records, and integration patterns that connect AI agents with APIs, databases, and enterprise platforms ·       Select and optimize models  — Evaluate foundation models (Gemini family, open models via Model Garden) for cost, latency, accuracy, and context window fit; design prompt strategies including chain-of-thought, few-shot, and system instructions ·       Architect RAG pipelines  — Design retrieval-augmented generation flows using Vertex AI Search, Vector Search, and custom data stores to ground agent responses in enterprise knowledge ·       Define guardrails and safety  — Establish input/output validation, content filtering, hallucination mitigation, and human-in-the-loop checkpoints to ensure responsible, reliable agent behavior ·       Design for observability  — Build tracing, logging, and monitoring into agent architectures to track reasoning chains, tool call performance, latency, cost, and quality metrics ·       Lead proof-of-concepts  — Execute PoCs to validate architectural decisions, de-risk new patterns, and demonstrate feasibility before committing to full builds ·       Enable the team  — Provide architectural guidance, conduct design reviews, create reusable templates and reference architectures, and help developers ramp up on the agent platform ·       Collaborate across teams  — Work with data engineering, platform engineering, Network Security, and business stakeholders to align AI solutions with enterprise standards, security requirements, and business goals ·       Stay ahead of the curve  — Track GCP platform updates, new agent capabilities, and emerging patterns in the rapidly evolving agentic AI landscape, and bring those insights back to the team   Must-Have Qualifications & Skills ·       Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent practical experience. ·       8–10+ years in solution architecture, software architecture, or a senior technical role specifically in cloud…