AI Engineer

Senior Staff AI Engineer

Job Description General Position Information

Reports Directly To (Title): Leader AI Engineering Matrix Reports To (Title): AVP AI & ML Platform engineering Direct Reports: No

Created / Last Revised: 4/20/2026 / Click here to enter a date.

Job Area: AI Engineering

Job Focus: AI Development

Job Category: Professional

Position Summary

The Senior Staff AI Engineer serves as a technical authority and strategic leader in the application of advanced Generative AI technologies, driving enterprise-scale innovation across the healthcare ecosystem. This role is responsible for defining and evolving architectural direction, guiding complex AI initiatives, and ensuring the successful adoption of cutting ‑ edge AI capabilities that transform how healthcare solutions are designed and delivered.

Operating at a level of influence beyond a single team, the Senior Staff AI Engineer shapes the long-term technical roadmap for Generative AI, particularly across GCP Vertex AI, Gemini, agentic systems, and large-scale Retrieval-Augmented Generation (RAG) platforms. The role balances deep hands-on technical contribution with organization-wide technical stewardship, mentoring Staff and Senior engineers, and partnering with executive stakeholders to align AI strategy with business outcomes.

This position sits within a flagship innovation organization and is intended for a highly experienced engineer who consistently operates in ambiguous problem spaces, sets technical standards, and drives durable, scalable AI platforms across multiple initiatives.

Key Responsibilities

Technical Leadership & Architecture

• Define and evolve the architectural vision and technical standards for enterprise Generative AI platforms.
• Lead the design of large-scale, multi-team AI systems, ensuring robustness, scalability, security, and responsible AI practices.
• Serve as a final technical reviewer for critical architectural decisions impacting multiple teams or strategic initiatives.
• Establish best practices for LLM usage, RAG architectures, embeddings, evaluation, observability, and lifecycle management.

Advanced AI Systems Development

• Lead the development of enterprise-grade Generative AI solutions on Google Cloud Platform, with deep expertise in Vertex AI, Gemini, and emerging tooling.
• Architect and oversee sophisticated Retrieval-Augmented Generation (RAG) ecosystems grounded in proprietary healthcare data.
• Design and standardize data grounding strategies, schemas, and pipelines that connect LLMs with real-world, real-time data sources.
• Drive the exploration and production adoption of agentic AI systems capable of complex reasoning, orchestration, and autonomous task execution.
• Champion the enterprise adoption and evolution of interoperability frameworks such as the Model Context Protocol.

Organizational Influence & Strategy

• Partner with AI leadership, product leadership, and executive stakeholders to shape AI strategy and long-term investment priorities.
• Translate complex technical capabilities into clear business value propositions and architectural options for senior leadership.
• Influence roadmap planning across multiple teams by identifying shared platforms, reusable components, and systemic risks.

Mentorship & Engineering Excellence

• Act as a technical mentor and sponsor for Staff and Senior Engineers, guiding their growth toward higher-level technical impact.
• Foster a culture of engineering excellence through architecture reviews, design mentorship, and cross-team collaboration.
• Lead investigations into complex, ambiguous AI challenges and guide teams toward elegant, scalable solutions.

Education & Experience: Bachelor’s degree in computer science, Engineering, or a related field, or equivalent practical experience.

Required 10+ years of professional software engineering experience, with 5–7+ years focused on AI/ML or advanced applied machine learning systems.

Required Proven track record of architecting and influencing large, production-grade AI platforms across multiple teams or domains.

Required Licenses, Certifications, & Training:

Advanced cloud or AI certifications (e.g., GCP Professional ML Engineer, Cloud Architect) preferred.

Preferred Knowledge, Skills, Abilities, Behaviors:

**Demonstrated growth m…