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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Apps AI Solution Architect AMS - **Company:** Atos Corp. - **Location:** Aurora, IL, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Applications Architecture, Application Services, Microsoft Azure, Mobile Application Development, Cloud Engineering, Design of User Interfaces, Mobile Application Software, Python (Programming Language), Mainframes, Node.Js, Productivity Software, Software Engineering, Web Applications, Datadog, Cloud Platform System, Modern Ui, GitHub Copilot, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Vue.js, Event Driven Architecture, Containerization, AngularJS, Machine Learning Operations, Front End Software Development, Splunk, Dynatrace, Servicenow, Microservices - **Published:** June 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f30eb389b8073b91 ## About the Role Do you have experience in Web applications?, * 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., * 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. ## Description * 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. ## Related Videos - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Lessons learned from building a thriving Vue.js SaaS application](https://www.wearedevelopers.com/videos/1666-lessons-learned-from-building-a-thriving-vue-js-saas-application) - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud) - [Common Mistakes in Vue.js and How to Avoid Them](https://www.wearedevelopers.com/videos/958-common-mistakes-in-vue-js-and-how-to-avoid-them) - [AI Killed DevOps... What Now? - Lee Faus](https://www.wearedevelopers.com/videos/1759-ai-killed-devops-what-now-lee-faus) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)