• Develop and deploy ML models and LLM-based solutions for product outcome prediction • Build workflows where users input product details and receive predictive insights • Enhance an existing AI agent into a decision-making/prediction system • Work with product and assortment data for feature engineering and modeling • Integrate LLM capabilities to improve reasoning and contextual understanding • Continuously evaluate and improve model performance

• Research, design, develop, and deploy innovative AI/ML and Generative AI solutions across various mission-focused problem sets • Support development of advanced AI capabilities using technologies such as large language models and cloud-native AI services including AWS Bedrock • Participate in all phases of the software engineering lifecycle, including research, requirements analysis, solution design, model development, integration, deployment, evaluation, and testing

Role Description Join Accenture’s AI & Data team to build and integrate production-grade applications powered by Large Language Models (LLMs) and enterprise services. In this role, you’ll shape end-to-end solutions—from user experience to APIs and platform operations—helping clients accelerate innovation, improve performance, and scale AI responsibly across the business. - Design, develop, and integrate full stack applications that leverage LLMs and AI agent frameworks - Build and maintain secure, scalable APIs and backend services that connect AI capabilities with enterprise systems - Collaborate with cross-functional stakeholders (product, data, engineering, security, and operations) to deliver high-impact solutions - Implement DevOps practices to automate deployment, monitoring, and reliability for AI-enabled applications - Conduct thorough testing, debugging, and performance tuning to ensure robust, efficient releases - Provide technical leadership and advisory input across multiple teams; drive decisions and reusable patterns where applicable - Stay current with advances in LLMs, tooling, and software engineering to continuously improve delivery practices - Mentor junior engineers and contribute to a culture of knowledge sharing and continuous learning Qualifications - Master proficiency in Large Language Models, including application integration patterns and optimization considerations - Expert proficiency in Digital Full Stack Development (front-end and server-side) - Advanced proficiency in DevOps practices (CI/CD, observability, environment automation, release management) - Advanced proficiency in Node.js-based front-end development and modern JavaScript/TypeScript practices - Experience building AI-enabled applications using agentic patterns and integrating with enterprise services - Strong stakeholder management skills with the ability to influence and communicate across technical/non-technical audiences - Bachelor’s Degree in a relevant field (Computer Science, Engineering, or similar) Preferred Qualifications - Experience with AI orchestration frameworks, prompt/response evaluation, and safety-by-design implementation - Familiarity with containerized deployments and cloud-native application architecture - Exposure to performance engineering for AI workloads and API scalability patterns Company Description Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

• Design and implement generative AI solutions using large language models (LLMs). • Apply prompt engineering techniques and build scalable Retrieval-Augmented Generation (RAG) systems. • Fine-tune and optimize models for performance, cost, and reliability. • Leverage AWS services such as Bedrock, SageMaker, and Lambda for deployment and inference. • Develop APIs and backend components for production-grade AI applications. • Implement observability, performance monitoring, and security best practices. • Drive responsible AI adoption through evaluation, bias detection, and compliance.