Principal AI Solutions Architect

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

📋 Description

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

• Offer architectural direction throughout the Enterprise AI Center of Excellence and delivery teams.

• Outline the technical framework, interfaces, dependencies, controls, and operational needs for reusable AI capabilities.

• Create comprehensive AI solutions and incorporate AI functionalities into enterprise applications and workflows.

• Develop reference architectures, engineering patterns, and technical standards that enhance security, consistency, reusability, maintainability, and alignment with enterprise goals.

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

• Assess solution designs and implementations, providing technical advice.

• Facilitate the efficient deployment and functioning of AI capabilities in collaboration with application, platform, DevOps, security, and delivery teams.

• Specify approaches for deployment, configuration, scaling, versioning, monitoring, rollback, support, and lifecycle management.

• Analyze emerging technologies and offer technical insights into capability sourcing, adoption decisions, and the enterprise AI architecture and capability roadmap.

• Collaborate with application, platform, infrastructure, data, DevOps, security, operations, 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.

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

• 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.

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

• Experience in providing technical leadership and architectural guidance without direct supervisory roles.

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

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

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

• Capability to set technical direction, 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.

• NOTE: This role REQUIRES experience with Model Context Protocol (MCP) Server, DevOps deployment, Cloud Architecture, and Enterprise AI Technologies.

• Preferred: experience with Azure AI, Azure OpenAI, Snowflake Cortex AI, LangGraph, Model Context Protocol (MCP), or similar enterprise AI technologies; Claude Code, GitHub Copilot, Cursor, or related agentic development tools; Camunda or similar workflow orchestration/business-process automation platforms; experience in healthcare, life sciences, clinical research, pharmacovigilance, patient access, or regulated industries; GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or other regulated-system requirements.

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

• Advanced proficiency in resolving complex architecture and engineering challenges with practical and maintainable solutions.

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

• Capacity to work efficiently 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 with company matching.*

• Tuition reimbursement.

• Flexible work environment.

• Discretionary PTO (Paid Time Off).

• Paid Holidays.

• Employee assistance programs.

• Comprehensive Medical, Dental, and vision coverage.

• HSA/FSA options.

• Telemedicine services (Virtual doctor appointments).

• Wellness program.

• Adoption assistance.

• Short-term disability coverage.

• Long-term disability coverage.

• Life insurance.

• Discount programs.