As a full-stack LLM Developer, you will be responsible for developing and integrating Large Language Models (LLMs) into full-stack applications. You will leverage open-source frameworks like Semantic Kernel, LangChain, and LlamaIndex to build, train, and fine-tune LLMs, creating applications that align with client needs and industry standards.

You will be working in an environment that embraces collaboration, creativity, and innovation while adhering to ethical guidelines and legal standards. As part of a cross-functional team, you will play a key role in deploying AI-powered solutions that are scalable, effective, and efficient.

Responsibilities

1. Develop LLM-based Applications. Create and integrate Large Language Models (LLMs) into full-stack applications, ensuring seamless operation and performance tuning for specific application needs.
2. AI Model Optimization. Build, train, and fine-tune LLMs to improve performance, accuracy, and general alignment with desired tasks. Ensure that the models meet functional and operational requirements.
3. Prompt Engineering. Formulate effective prompts for generative AI models and design comprehensive, effective applications across the technology stack to meet project goals.
4. Ethical AI Development. Ensure that AI applications comply with ethical guidelines, focusing on data privacy, user consent, and responsible AI practices.
5. System Design. Design and develop detailed system components that leverage LLMs, enhancing integration with other system components to create robust, scalable solutions.
6. Domain Adaptation. Apply domain-specific data and techniques for domain adaptation to enhance model effectiveness and accuracy.
7. AI Testing and Optimization. Develop and execute testing plans for AI applications, continually optimizing for efficiency, scalability, and performance.
8. DevOps and MLOps. Collaborate in developing DevOps and MLOps pipelines for the deployment of AI models and applications, ensuring smooth integration into the production environment.
9. Incident Resolution and Troubleshooting. Proactively monitor application performance, identify potential issues, and troubleshoot technical incidents across the full stack—both front-end, back-end, and LLM integrations.
10. Explore Emerging Technologies. Stay up-to-date with the latest in AI technologies, identifying opportunities for integration into business solutions.
11. Travel. Occasional travel may be required.

Basic Qualifications

• Bachelor's Degree in Computer Science, Engineering, or a related field.
• Minimum of 3 years of work experience in full-stack software development, with a significant focus on AI-powered application development.
• At least 1 year of experience in Machine Learning, with a solid understanding of deep learning algorithms and concepts.
• 4-6 months of experience working with Generative AI models and associated application frameworks, such as LLM models.

Preferred Qualifications

• Experience contributing to open-source AI projects.
• Knowledge of AI frameworks such as Semantic Kernel, LangChain, or LlamaIndex.
• Familiarity with cloud platforms and containerization technologies (e.g., Docker, Kubernetes) is a plus.

Why Join Accenture?

1. Innovative Work. Be part of a team that shapes the future of enterprise AI and pushes the boundaries of what’s possible with generative AI and LLM technologies.
2. Career Growth. Accenture offers unparalleled learning opportunities and the ability to work with industry-leading experts in AI and software development.
3. Diverse and Inclusive Culture. Work in an inclusive and diverse environment where creativity, innovation, and teamwork are celebrated.
4. Compensation & Benefits. Competitive salary packages, bonus programs, and comprehensive benefits to support your well-being.
5. Global Impact. Accenture’s work reaches clients around the globe, providing you with the opportunity to contribute to cutting-edge solutions that solve real-world business challenges.

Accenture is an Equal Opportunity Employer

We are committed to diversity and inclusion and encourage applicants from all backgrounds to apply.