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Atos · 1 day ago

Apps AI Solution Architect 539995

United States

Full-time

Remote

Senior Level, Lead/Staff

10+ years exp

Atos is focused on transforming enterprise applications in the GenAI era. The Apps AI Architect will leverage application architecture expertise and AI engineering skills to design, build, and manage AI-native applications, driving innovation and delivering proof-of-value initiatives.

Business DevelopmentConsultingEnterprise SoftwareInformation ServicesInformation TechnologyOutsourcingSoftware

Hiring Manager

Anthony Sisco

Responsibilities

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

Qualification

Application ArchitectureAI/ML ImplementationAzure OpenAIUI/UX ArchitecturePythonMLOps/GenAIOpsApplication ModernizationObservability PlatformsStakeholder ManagementCommunication Skills

Required

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

Preferred

Certifications in AI Engineering (Azure, AWS, or Google) or equivalent credentials

Prior experience working in Application Services, AMS, or ADM environments

Exposure to agentic workflows, AI observability, or RAG (retrieval-augmented generation) frameworks

The role requires active engagement across the full lifecycle — from pre-sales solution shaping through design, development, implementation, and ongoing evolution of AI-native applications

Given the evolving nature of AI-native architectures, we welcome candidates who may not meet every requirement but demonstrate strong foundational skills and the ability to grow into the role