Principal AI Solutions Architect

🕒 vor 18 Tagen

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🔴 Experte

💻 Lösungsingenieur

👻 Geisterscore 10%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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Lebenslauf hochladen

UBC

WebsiteLinkedInAlle Stellen

1001 - 5000 Mitarbeiter

Gegründet 2003

🏥 Gesundheitswesen

💼 Beratung

🧬 Biotechnologie

Healthcare • Consulting • Biotechnology

UBC ist ein Unternehmen, das sich der Verbesserung von Patientenergebnissen widmet, indem es spezielle Therapien mit bedürftigen Patienten verbindet. Sie bieten moderne und maßgeschneiderte Lösungen, die sich auf den Zugang, die Sicherheit und die Evidenzerzeugung für biopharmazeutische Produkte konzentrieren. UBC ist spezialisiert auf die Evidenzentwicklung, das Risikomanagement und den Patientenzugang und nutzt reale Daten und innovative Technologien, um die Gesundheitsreise zu optimieren und einen effektiven Medikamenteneinsatz zu gewährleisten.

Beschreibung

• Define the technical architecture, engineering patterns, and implementation approach for reusable AI capabilities across the enterprise • Establish how AI capabilities are designed, built, deployed, integrated, monitored, secured, and reused across business systems • Partner with application, platform, infrastructure, data, DevOps, and security teams to align reusable AI capabilities with enterprise architecture, operational standards, and business needs • 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 technical structures, 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 • Define deployment, configuration, scaling, versioning, monitoring, release, rollback, support, and lifecycle management approaches for AI capabilities • Evaluate emerging technologies and provide technical input into 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

🎯 Anforderungen

• Bachelor’s degree in computer science, software engineering, computer engineering, information systems, or a related technical discipline, or equivalent practical experience • Master’s degree preferred • 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 • 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 comparable 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 similar 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 connect technical decisions to enterprise architecture, long-term reuse, scalability, and business strategy • Advanced ability to resolve complex architecture and engineering challenges • 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

🏖️ Vorteile

• 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