Accenture Southeast Asia
Linkedin · Posted 2mo ago
LLM Full Stack Engineer Associate Director
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Indexed description
About The RoleJoin 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 Required QualificationsMaster 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 QualificationsExperience 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
Key Responsibilities
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