Principal AI Solutions Architect

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

📋 Description

• Define the technical architecture, engineering patterns, and implementation strategies for reusable AI capabilities throughout the organization.

• Establish the design, construction, deployment, integration, monitoring, security, and reuse of AI capabilities across business systems.

• Collaborate with application, platform, infrastructure, data, DevOps, and security teams to ensure alignment of reusable AI capabilities with enterprise architecture, operational standards, and organizational requirements.

• Act as the primary technical authority for AI solution and deployment architecture.

• Provide architectural direction across the Enterprise AI Center of Excellence and its delivery teams.

• Define technical structures, interfaces, dependencies, controls, and operational criteria for reusable AI capabilities.

• Design comprehensive AI solutions and incorporate AI capabilities into enterprise applications and workflows.

• Establish reference architectures, engineering patterns, and technical standards that promote security, consistency, reuse, maintainability, and alignment with enterprise objectives.

• Directly contribute to proof-of-concept and production-ready AI solutions, deployment methodologies, and technical components.

• Review solution designs and implementations while offering technical guidance.

• Establish strategies for deployment, configuration, scaling, versioning, monitoring, release, rollback, support, and lifecycle management of AI capabilities.

• Assess emerging technologies and provide technical input regarding capability sourcing, adoption decisions, and the enterprise AI architecture and capability roadmap.

• Collaborate across Product Management, AI Science, Application Development, Platform Engineering, DevOps, Security, Data, Quality, and business teams.

⛳️ Requirements

• Bachelor’s degree in computer science, software engineering, computer engineering, information systems, or a related technical field, or equivalent practical experience.

• Master’s degree is preferred.

• Over 10 years of experience in software engineering, solution architecture, platform engineering, DevOps, or related technical roles.

• At least 4 years of experience in designing and implementing AI, machine learning, cloud-native, data-intensive, or distributed enterprise solutions.

• Extensive experience in designing, deploying, and supporting production applications, services, or platforms.

• Experience in defining architectural standards, deployment strategies, and engineering practices across multiple delivery teams.

• Proven experience providing technical leadership and architectural guidance without direct supervisory authority.

• Profound understanding of modern AI systems, including large language models, retrieval-augmented generation, AI agents, orchestration, tool integration, structured outputs, human review, and workflow integration.

• Strong software engineering foundation with expertise in cloud-native architectures, APIs, containers, CI/CD, deployment automation, DevOps, and production operations.

• Experience integrating reusable capabilities with enterprise applications, workflow platforms, identity services, APIs, messaging systems, and data platforms.

• Strong grasp of secure architecture principles, identity and access management, data protection, observability, audit logging, resiliency, and operational controls.

• Ability to set technical direction, establish reusable engineering patterns, architecture standards, and deployment strategies that support scalable enterprise AI.

• Knowledge of structured and unstructured data, retrieval patterns, vector search, semantic retrieval, data movement, lineage, and access controls.

• Experience with Model Context Protocol (MCP) Server, DevOps deployment, cloud architecture, and enterprise AI technologies is required.

• Preferred experience with Azure AI, Azure OpenAI, Snowflake Cortex AI, LangGraph, Model Context Protocol (MCP), or similar enterprise AI technologies.

• Preferred experience using Claude Code, GitHub Copilot, Cursor, or similar agentic development tools.

• Preferred experience with workflow orchestration or business-process automation platforms such as Camunda or comparable technologies.

• Preferred experience in healthcare, life sciences, clinical research, pharmacovigilance, patient access, or another regulated industry.

• Familiarity with GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or other regulated-system expectations.

• Ability to link technical decisions to enterprise architecture, long-term reuse, scalability, and business strategy.

• Advanced capability to resolve complex architectural and engineering challenges.

• Ability to effectively communicate architectural concepts, tradeoffs, and recommendations to executives, engineers, scientists, architects, and business stakeholders.

• Ability to work collaboratively across Product Management, AI Science, Application Development, Platform Engineering, DevOps, Security, Data, Quality, and business teams.

• Ability to assess emerging technologies and adapt architectural direction while maintaining engineering discipline and operational reliability.

🏝️ Benefits

• Competitive salaries.

• Opportunities for career advancement.

• 401K plan with company matching.*

• Tuition reimbursement programs.

• Flexible working environment.

• Discretionary Paid Time Off (PTO).

• Paid holidays.

• Employee assistance programs.

• Comprehensive medical, dental, and vision coverage.

• Health Savings Account (HSA) / Flexible Spending Account (FSA).

• Telemedicine services (virtual doctor appointments).

• Wellness initiatives.

• Adoption assistance programs.

• Short-term disability coverage.

• Long-term disability coverage.

• Life insurance options.

• Discount programs.