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 mindset with the ability to proactively identify, evaluate, and drive adoption of emerging AI technologies, frameworks, and paradigms across teams and platforms in a rapidly evolving AI landscape. Required Required · Ability to independently operate in highly ambiguous problem spaces , define technical direction, and align engineering outcomes with long-term business strategy. Required Required · Expert-level knowledge and hands-on leadership experience with GCP Vertex AI, including generative AI models (e.g., Gemini), Vertex AI Studio, and enterprise deployment patterns; recognized as a subject matter expert across teams. Required · Advanced, architecture-level expertise in designing, scaling, and governing Retrieval-Augmented Generation (RAG) systems, including tradeoff analysis, evaluation frameworks, and long-term maintainability. Required · Proven experience defining enterprise standards and best practices for Vector Stores, embeddings, indexing strategies, and lifecycle management at scale. Required · Deep expertise in grounding strategies , including data modeling, schema design, and large-scale pipeline orchestration to ensure LLM factuality, traceability, and regulatory alignment. Required · Strong leadership-level experience with DevOps and CI/CD for AI/ML systems (MLOps), including platform design, governance, observability, and reliability across environments. Required · Extensive experience designing cloud-native architectures for AI platforms, including serverless, containerized, and hybrid solutions with a focus on scalability, resilience, and security. Required · Ability to define and review system and platform diagrams (e.g., Visio, architecture artifacts) that communicate complex architectures clearly to technical and executive audiences. Required · Strong working knowledge of the Model Context Protocol , with experience guiding its application to enable standardized, extensible interactions between LLMs and external tools and data sources Required · Advanced familiarity with Agentic AI frameworks and patterns (e.g., LangChain), including evaluation of autonomous and multi-agent systems for real-world enterprise use cases. Required · Broad and deep full-stack experience across enterprise technology ecosystems, with the ability to architect and integrate solutions involving: SQL and NoSQL databases (e.g., SQL Server, CosmosDB, MongoDB) ETL and large-scale data pipelines (e.g., GCP DataFlow, Azure Data Factory) Eventing and streaming platforms (e.g., Azure EventHub, GCP Pub/Sub, Kafka) Microservice and distributed systems (e.g., Docker/Kubernetes, Java, Python, NodeJS, C#) Required · Experience architecting and integrating AI solutions within CRM, ERP, eCommerce, or EMR/EHR systems , including enterprise integration patterns, security, and compliance considerations. Preferred · Expert understanding of Agile methodologies and modern software development lifecycles , with the ability to influence process improvements across multiple teams. Required · Demonstrated ability to communicate complex technical concepts succinctly and persuasively to engineers, product leaders, and executive stakeholders, both verbally and in writing. Required · Ability to lead engineering communities of practice , technical forums, or internal events focused on AI, software engineering excellence, or platform evolution. Required · Exceptional problem-solving and analytical skills , with a history of resolving systemic, high‑impact technical challenges. Required · Advanced troubleshooting expertise, including log analysis, performance tuning, and load testing in large, distributed AI systems. Required · Ability to lead through influence , guiding multiple engineers or teams toward outcomes without direct authority. Required · Strong ability to understand and shape technical context , including codebases, architectures, and their direct relationship to business objectives and long-term strategy. Required Travel Required Check the frequency of travel required of the employee to perform the essential functions of the job. ☐ No Travel: The job does not require any travel. ☒ Occasional Travel: The job may require travel from time- to-time, but not on a regular basis. ☐ The job may require up to 25% travel. ☐ The job may require up to 50% travel. ☐ The job may require up to 75% travel. ☐ The job may require 76% or more travel. My signature below acknowledges that I have read the above job description and agree that I can perform the responsibilities and meet the requirements. I also understand that this job description may change at any given time based on organizational or department needs. SIGNOFF & ACKNOWLEDGEMENT X Click here to enter text.