Senior AI Architect

This is a fully remote position, open to applicants in Pennsylvania.

📋 Description

• Serve as the senior technical authority for AI architecture, addressing intricate architectural and engineering challenges.

• Design and help establish essential infrastructure, platform services, and reusable capabilities across Azure, Google Cloud Platform, Databricks, AKS, Microsoft Entra, and other related technologies.

• Define multi-cloud reference architectures, integration patterns, engineering standards, security guardrails, and reusable solution models.

• Lead the architectural and technical implementation for generative AI, machine learning, retrieval-augmented generation, agentic AI, data and knowledge services, APIs, microservices, and production AI applications.

• Create designs for identity, access, networking, secrets, compute, storage, data, model-serving, containerization, observability, and deployment methodologies.

• Collaborate with cloud, data engineering, cybersecurity, infrastructure, software engineering, data science, product, and business teams to transition AI initiatives into dependable production services.

• Establish and advocate for MLOps, GenAIOps, CI/CD, infrastructure-as-code, automated testing, monitoring, model and prompt lifecycle management, and operational support practices.

• Deliver hands-on technical leadership through architecture reviews, design sessions, troubleshooting, implementation advice, proofs of concept, technical documentation, and critical-path engineering.

• Report to the Manager - AI Architecture as an individual contributor without direct reports.

⛳️ Requirements

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

• Proven experience in architecting production systems.

• Background in senior technical leadership positions.

• Experience serving as a technical lead.

• Bachelor's degree in computer science, software engineering, data engineering, data science, information systems, engineering, or a closely related technical field.

• Professional certifications in Microsoft Azure, Google Cloud, Databricks, Kubernetes, or AI/ML architecture.

• Experience in multi-cloud architecture, particularly with Microsoft Azure and Google Cloud Platform.

• Knowledge of workload placement, interoperability, networking, identity, security, and operational trade-offs.

• Familiarity with Databricks/Lakehouse architecture.

• Experience in integrating governed enterprise data with AI and machine-learning workloads.

🏝️ Benefits

• Remote work.

• Equal Opportunity Employer, including Veterans and Individuals with Disabilities.