Advanced AI Full Stack Engineer
Accenture is hiring an AI Full Stack Engineer in Singapore to design, build, and deploy LLM-powered applications end-to-end — from prompt engineering and fine-tuning foundation models to full-stack integration and production deployment — using Python, cloud AI services, and frameworks like LangChain and LangGraph.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Fullstack
- Posted
Skills
Must have
- Minimum 4 years designing and building resilient AI systems or products, including controls, guardrails, context engineering, Evals, CI/CD, tracing, logging and unit testing in production
- Minimum 4 years designing AI solutions using patterns like RAG and handling data pipelines
- Minimum 4 years in engineering teams with one or more of Python, JavaScript, Java, Spring or GoLang, and mastery of one or more AI frameworks like Autogen, LangGraph or Semantic Kernel
- Minimum 4 years working with application services from at least one public cloud (AWS, GCP, Azure), including AI/GenAI services such as Anthropic
- Minimum 3 years in AI engineering with strong understanding of fine-tuning and prompt engineering, including token utilization and latency optimization
- Minimum 2 years leading a team or team management, preferably in AI-driven project environments
- Bachelor's degree or equivalent (minimum 12 years work experience); associate's degree requires minimum 6 years work experience
Nice to have
- Experience training, fine-tuning and evaluating LLMs and multimodal foundation models using self-supervised and transfer learning
- Experience designing value justification frameworks for AI solutions (cost estimation, ROI calculation, tradeoff analysis)
- Experience building AI solutions using Model Context Protocol and Agent-to-Agent protocols
- Experience developing applications for both mobile and web platforms
Full description
We Are We are entering into a new decade of Data & AI that will reshape work and society. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work. With over 77,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization is powered by experienced innovation, strategic investment, exceptional talent, and our power ecosystem.
You Are: An AI Full Stack Engineer who combines expertise in artificial intelligence, software development, and full‑stack technologies, capable of designing, developing, deploying, and maintaining AI‑powered applications end‑to‑end. You will be responsible for building AI‑driven applications across the full technology stack—from the frontend user interface to the backend, server‑side logic, and machine learning models. Unlike traditional software engineers or AI specialists who focus on a single area, you have a comprehensive understanding of both AI/ML frameworks and software architecture.
The Work: You will play a pivotal role in designing, building, and deploying next‑generation AI systems powered by Large Language Models (LLMs). You will contribute across the full AI lifecycle — from researching and fine‑tuning foundation models to prompt engineering, system integration, and deployment into production environments. You will improve performance, accuracy and alignment of the LLMs and AI systems. You bring a mix of hands‑on engineering skills, deep knowledge of modern AI architectures, and a passion for applying AI responsibly to solve real‑world problems. In addition, you will utilize your strong skills to develop and integrate AI Systems into products and services. You have expertise in designing, developing, and optimizing AI prompts.
Position Responsibilities:
- Design, develop, and optimize AI prompts and next‑generation AI applications powered by foundation models, including Large Language Models (LLMs).
- Architect and implement generative agent systems using frameworks for multi‑model coordination to tackle complex tasks.
- Develop application and component strategies, overseeing both user experience and back‑end systems.
- Define, evaluate, and optimize AI system architectures, leveraging relevant frameworks (OpenAI, LangChain, etc.) and best practices.
- Conduct thorough code reviews, provide expert guidance on enhancements and issue resolution, and ensure adherence to engineering standards.
- Build and maintain scalable machine learning infrastructure, including distributed training pipelines and seamless integration with APIs and tools.
- Apply advanced evaluation methodologies to ensure model robustness, safety, fairness, and minimize hallucination risks.
- Collaborate closely with cross‑functional teams—including business leaders, engineers, architects, and designers—to align AI systems with business objectives.