LLM Full Stack Engineer Manager
Singapore
Job No. 14210587
Full-time - Remote
工作描述
About the Role
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.
Key Responsibilities
- 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
职位要求
Required 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
