Application Architect-Cloud Applications

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. The Senior Engineer is responsible for designing, building, and scaling AI-enabled solutions that enhance software delivery effectiveness. The role combines strong software engineering fundamentals with practical expertise in AI-assisted development, automation, testing, and operational excellence. The Senior Engineer actively drives adoption of AI-DLC practices and partners with product, architecture, and platform teams to accelerate delivery and improve quality. AI-Enabled Software Development Build and maintain AI-powered engineering solutions. Develop and optimize prompts, agents, copilots, and automation workflows. Integrate LLM capabilities into enterprise applications. AI SDLC Adoption Apply AI throughout requirements analysis, design, development, testing, and operations. Drive implementation of AI-assisted coding and testing practices. Support engineering teams in adopting AI-native ways of working. Engineering Delivery Design and develop scalable cloud-native applications. Perform code reviews and technical design reviews. Ensure security, quality, maintainability, and performance standards. DevSecOps & Automation Build CI/CD pipelines and engineering automation. Implement automated quality gates and testing frameworks. Monitor and optimize platform reliability. Continuous Improvement Evaluate emerging AI technologies. Share best practices and lessons learned. Contribute to engineering standards and communities of practice. Required Qualifications Bachelor's degree in Computer Science, Engineering, or related field. 7+ years of software engineering experience. Hands-on experience developing AI-enabled applications. Strong experience with cloud-native technologies and DevSecOps. Technical Skills Python, Java, TypeScript, or C# LLM APIs and frameworks Agentic workflows RAG implementations Vector databases Prompt engineering CI/CD pipelines Containerization and Kubernetes GitHub, GitHub Copilot, Azure DevOps, Jira Preferred Qualifications AI/ML certification or equivalent practical experience. Experience implementing enterprise AI governance requirements. Experience mentoring junior engineers and leading technical initiatives. Key Competencies Technical problem solving AI innovation Automation-first mindset Collaboration Communication Ownership and accountability