About the role:As a Senior Staff AI Architect, you will be a senior technical leader and voice of authority for the architecture, engineering, and operationalization of critical artificial intelligence capabilities across a multi-cloud environment. You will design and promote secure, scalable, reusable AI infrastructure and services spanning Microsoft Azure, Google Cloud Platform, Databricks, Azure Kubernetes Service (AKS), Microsoft Entra, and related enterprise technologies. You will be an individual contributor with no direct reports.
You will report to the Manager - AI Architecture and work remotely.
Key Responsibilities:- Be a senior technical authority for AI architecture, providing clear technical direction and resolving complex architecture and engineering decisions across critical AI programs.
- Architect and help stand up foundational infrastructure, platform services, and reusable capabilities across Microsoft Azure, Google Cloud Platform, Databricks, AKS, Microsoft Entra, and supporting enterprise technologies.
- Define multi-cloud reference architectures, integration patterns, engineering standards, security guardrails, and reusable solution patterns for enterprise AI workloads.
- Lead architecture and technical delivery for generative AI, machine learning, retrieval-augmented generation, agentic AI, data and knowledge services, APIs, microservices, and production AI applications.
- Design secure identity, access, networking, secrets, compute, storage, data, model-serving, container, observability, and deployment patterns appropriate for enterprise AI platforms.
- Partner with cloud, data engineering, cybersecurity, infrastructure, software engineering, data science, product, and business teams to move AI efforts from concept and proof of value into reliable production services.
- Establish and promote MLOps, GenAIOps, CI/CD, infrastructure-as-code, automated testing, monitoring, model and prompt lifecycle, and operational support practices
- Provide hands-on technical leadership through architecture reviews, design sessions, troubleshooting, implementation guidance, proofs of concept, technical documentation, and critical-path engineering when needed.
Qualifications:- 10+ years of progressive experience in software, cloud, data, platform, or AI engineering, including experience architecting production systems and serving in senior technical leadership roles.
- Expereince as a technical lead
- Bachelor's degree in computer science, software engineering, data engineering, data science, information systems, engineering, or a related technical field.
Professional Certifications: - Microsoft Azure, Google Cloud, Databricks, Kubernetes, or AI/ML architecture certifications
- Multi-cloud architecture spanning Microsoft Azure and Google Cloud Platform, with understanding of workload placement, interoperability, networking, identity, security, and operational tradeoffs.
- Databricks / Lakehouse architecture and integration of governed enterprise data with AI and machine-learning workloads.
We are committed to transparency and equity in all of our people practices. The base salary range for this position, which is dependent upon experience, qualifications and skills, is estimated to be $103,200 to $129,000 per year.
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