Apps AI Solution Architect

🕒 Abril 25

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🔴 Especialista

💻 Engenheiro de Soluções

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Atos

SiteLinkedInTodas as Vagas

10.000+ funcionários

🔒 Cibersegurança

IT Services • Cloud • Cybersecurity

A Atos é líder global em transformação digital, oferecendo um portfólio de serviços e soluções em cloud e infraestrutura, Digital Workplace e serviços de tecnologia. A empresa se concentra em ajudar clientes a aprimorar suas capacidades digitais por meio de tecnologia inovadora e serviços de consultoria, com ênfase em sustentabilidade e responsabilidade social. A Atos também é conhecida por seu papel em grandes eventos, fornecendo suporte de TI e elevando a experiência de milhões de usuários no mundo todo, incluindo parcerias com organizações como a UEFA e serviços sob medida para o setor de saúde.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Flexible work arrangements • Professional development