Principal AI Architect

Responsibilities

• Define technical strategy and lead architectural design for cloud, data, and AI/ML systems across end-to-end engagements.
• Architect scalable multi-cloud and hybrid cloud-native solutions using platforms such as AWS, Azure, GCP, and Kubernetes.
• Design data warehouses, data lakes, batch and streaming pipelines, and AI/ML systems including model serving, MLOps, feature stores, and LLM applications.
• Establish infrastructure-as-code, CI/CD, DevOps, architecture, governance, security, and compliance standards.
• Lead cloud migrations and platform modernization while optimizing performance, scalability, cost, and reliability.
• Partner with clients, leadership, engineering, data, AI, and product teams on technical strategy and direction.
• Document architecture standards and guidelines, evaluate emerging technologies, and mentor experienced engineers and architects.
• Use AI-forward tools such as Claude and Cursor to deliver high-quality work efficiently.

Requirements

• 8+ years of software engineering experience, including at least 5 years in technical leadership roles.
• Deep expertise in cloud platforms and cloud-native architectures, including AWS, Azure, or GCP.
• Strong background in microservices, serverless, containers, and event-driven systems.
• Proficiency with infrastructure as code and CI/CD tools.
• Strong data architecture experience across relational, NoSQL, and big data systems, including data modeling, ETL/ELT, and orchestration.
• Strong experience designing production AI/ML systems, including LLMs, MLOps, and model serving.
• Understanding of networking, security, identity and access management, governance, compliance, and observability in cloud environments.
• Strong software engineering skills with Python, APIs, and containerization.
• Demonstrated senior technical leadership, mentoring, stakeholder communication, and ability to translate complex technical concepts across audiences.
• Experience using AI-forward tools such as Claude and Cursor.
• Multi-cloud architecture, responsible AI or AI ethics, and enterprise architecture certifications are preferred.
• Experience integrating AI/ML solutions with SAP EAM data structures through SAP BTP or cloud-native APIs is helpful.

Benefits

• Comprehensive benefits package including paid time off, medical, dental, and vision insurance, and a 401(k) for eligible employees.
• Employment may be conditional on successful completion of a background check.