Apps AI Solution Architect

🕒 vor 1 Monat

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🟠 Senior

🔴 Experte

💻 Lösungsingenieur

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Atos

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10.000+ Mitarbeiter

🔒 Cybersecurity

IT Services • Cloud • Cybersecurity

Atos ist ein global führendes Unternehmen im Bereich der digitalen Transformation und bietet eine breite Palette von Lösungen und Dienstleistungen in verschiedenen Branchen an. Das Unternehmen ist spezialisiert auf Cloud- und Infrastrukturdienste, digitale Geschäftsplattformen, Technologieberatung und Cybersicherheit. Dabei liegt der Fokus auf der Verbesserung von Benutzererfahrungen und der Unterstützung unternehmerischer digitaler Reisen. Atos engagiert sich für Nachhaltigkeit und Innovation und arbeitet mit verschiedenen Organisationen zusammen, um digitale Fortschritte voranzutreiben, wie beispielsweise seine Rolle als offizieller IT-Partner der UEFA und der Olympischen Spiele.

Beschreibung

• Architect AI-Native Applications: Design and implement architectures that integrate AI models (LLMs, predictive, and agentic systems) into application workflows to enable reasoning, automation, and contextual decision-making. • End-to-End Application Design: Lead the design of UI/UX flows, user-facing AI interactions, conversational interfaces, and AI-augmented user journeys across web and mobile applications. • Drive Modernization Through AI: Reimagine legacy and digital applications by embedding AI capabilities that enable modernization, optimization, and transformation across app portfolios. • Design modernization frameworks leveraging AI for architecture discovery, business-rules extraction, and application rationalization. • Embed intelligence in re-platformed or refactored applications to create truly AI-native modernization. • Legacy-to-Modern Mapping: Architect solutions that transform legacy applications into modern Java, .NET, microservices, or cloud-native platforms while preserving core business rules and logic. • Infuse AI Across Dev & Ops: Partner with delivery and support teams to embed AI in software engineering, testing, incident management, and observability — driving efficiency, resilience, and proactive operations. • Tooling & Frameworks: Evaluate, integrate, and optimize AI-assisted tools (e.g., code translators, test generators, documentation bots) within modernization pipelines to accelerate delivery. • Integration & Ecosystem: Define strategies to integrate modernized applications into enterprise ecosystems, including APIs, event-driven architectures, and cloud environments. • Lead Proofs of Value (PoVs): Design and execute AI-centric PoVs to validate new technologies, tools, and architectures for clients. • Collaborate & Evangelize: Partner with pre-sales, delivery, and client stakeholders to identify AI opportunities, shape proposals, and articulate the business value of AI-native transformation. • Develop Reusable Assets: Create frameworks, accelerators, and reference architectures to scale adoption of GenAI and LLM-enabled solutions across multiple accounts.

🎯 Anforderungen

• 10–15 years of experience in Application Architecture, Engineering, or Digital Transformation, with at least 2–3 years in AI/ML or GenAI implementation. • Strong experience with Azure OpenAI, OpenAI APIs, Vertex AI, AWS Bedrock, LangChain, LlamaIndex, or similar LLM platforms. • Deep understanding of modern UI/UX architecture, responsive front-end design, and frameworks such as React, Angular, Vue, or equivalent. • Proficiency in Python, Node.js, or Java, with exposure to LLM integration, prompt engineering, and API orchestration. • Experience with leading AI-assisted productivity tools such as Claude, Gemini Code Assist, and GitHub Copilot. • Familiarity with observability and AIOps platforms including DataDog, Dynatrace, Moogsoft, Splunk AIOps, and ServiceNow AIOps. • Hands-on exposure to LLM-based ITSM agents and RAG (Retrieval-Augmented Generation) frameworks. • Experience with MLOps/GenAIOps for continuous model improvement within modernization initiatives. • Strong background in application modernization (re-platforming, containerization, microservices, and cloud-native design). • Solid understanding of legacy technologies such as Mainframe, Java, and .NET. • Knowledge of PromptOps, model observability, AI lifecycle management, and related operational frameworks. • Excellent communication, stakeholder management, and customer-facing engagement skills.

🏖️ Vorteile

• Flexible work arrangements • Professional development