Senior AI Architect - Multi-Cloud Infra for GenAI (Remote)

Westinghouse Electric Company

Cranberry Township (Butler County)

Remote

USD 103,000 - 129,000

Full time

3 days ago

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Job summary

Westinghouse Electric Company seeks a Senior Staff AI Architect to lead the architecture, engineering, and deployment of critical AI capabilities across multi-cloud environments. You will design scalable, secure AI infrastructure and serve as a senior technical authority with no direct reports, reporting to the Manager - AI Architecture.

The role emphasizes hands-on leadership, cross-team collaboration, and the establishment of MLOps, CI/CD, and production-grade AI solutions.

Qualifications

10+ years of progressive experience in software, cloud, data, platform, or AI engineering.
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.

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 Azure, Google Cloud Platform, Databricks, AKS, 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, ML, 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 for enterprise AI platforms.
Partner with cloud, data engineering, cybersecurity, infrastructure, software engineering, data science, product, and business teams to move AI efforts into 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.