Principal AI Solutions Architect

🕒 il y a 22 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🔴 Expert

💻 Ingénieur Solutions

👻 Score fantôme 10%

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🗣️🇺🇸🇬🇧 Anglais requis

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UBC

1001 - 5000 employés

Fondée en 2003

🏥 Santé

💼 Conseil

🧬 Biotechnologie

Healthcare • Consulting • Biotechnology

UBC est une entreprise dédiée à l'amélioration des résultats pour les patients en reliant les thérapies spécialisées aux patients dans le besoin. Elle offre des solutions modernes et personnalisées axées sur l'accès, la sécurité, et la génération de preuves pour les produits biopharmaceutiques. UBC se spécialise dans le développement de preuves, la gestion des risques, et l'accès des patients, en utilisant des données du monde réel et des technologies innovantes pour optimiser le parcours de soins et assurer l'utilisation efficace des médicaments.

Description

• Serve as the principal technical authority for AI solution and deployment architecture • Provide architectural guidance across the Enterprise AI Center of Excellence and delivery teams • Define the technical structure, interfaces, dependencies, controls, and operational requirements for reusable AI capabilities • Design end-to-end AI solutions and integrate AI capabilities into enterprise applications and workflows • Establish reference architectures, engineering patterns, and technical standards promoting security, consistency, reuse, maintainability, and enterprise alignment • Contribute directly to proof-of-concept and production-oriented AI solutions, deployment patterns, and technical components • Review solution designs and implementations and provide technical guidance • Enable effective deployment and operation of AI capabilities with application, platform, DevOps, security, and delivery teams • Define deployment, configuration, scaling, versioning, monitoring, release, rollback, support, and lifecycle management approaches • Evaluate emerging technologies and provide technical input into capability sourcing, adoption decisions, and the enterprise AI architecture and capability roadmap • Partner with application, platform, infrastructure, data, DevOps, security, operational, and business teams

🎯 Exigences

• Bachelor’s degree in computer science, software engineering, computer engineering, information systems, or a related technical discipline, or equivalent practical experience • 10+ years of experience in software engineering, solution architecture, platform engineering, DevOps, or related technical roles • 4+ years of experience designing and implementing AI, machine learning, cloud-native, data-intensive, or distributed enterprise solutions • Significant experience designing, deploying, and supporting production applications, services, or platforms • Experience defining architectural standards, deployment strategies, and engineering practices across multiple delivery teams • Experience providing technical leadership and architectural guidance without direct supervisory responsibility • Deep 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 background with 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 understanding of secure architecture principles, identity and access management, data protection, observability, audit logging, resiliency, and operational controls • Ability to establish technical direction, reusable engineering patterns, architecture standards, and deployment approaches supporting 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 comparable enterprise AI technologies; Claude Code, GitHub Copilot, Cursor, or similar agentic development tools; Camunda or similar workflow orchestration/business-process automation platforms; healthcare, life sciences, clinical research, pharmacovigilance, patient access, or regulated industry; GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or other regulated-system expectations • Ability to connect technical decisions to enterprise architecture, long-term reuse, scalability, and business strategy • Advanced ability to resolve complex architecture and engineering challenges through practical and maintainable solutions • Ability to communicate architectural concepts, tradeoffs, and recommendations clearly to executives, engineers, scientists, architects, and business stakeholders • Ability to work effectively across Product Management, AI Science, Application Development, Platform Engineering, DevOps, Security, Data, Quality, and business teams • Ability to evaluate emerging technologies and evolve architectural direction while maintaining engineering discipline and operational reliability

🏖️ Avantages

• Competitive salaries • Growth opportunities for promotion • 401K with company match* • Tuition reimbursement • Flexible work environment • Discretionary PTO (Paid Time Off) • Paid Holidays • Employee assistance programs • Medical, Dental, and vision coverage • HSA/FSA • Telemedicine (Virtual doctor appointments) • Wellness program • Adoption assistance • Short-term disability • Long-term disability • Life insurance • Discount programs

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