As an AI / LLM Architect at Accenture, you will shape the future of technology architecture for advanced AI, particularly Large Language Models (LLM). Your role will be pivotal in translating business roadmaps into cutting-edge technical requirements and architectures. You'll contribute to the design of sophisticated LLMs, enhancing their capabilities to process and generate natural language. This position offers a unique opportunity to work on neural network parameters and leverage extensive unlabeled text data to innovate AI solutions.
Position Responsibilities
- Architectural Design. Design end-to-end Generative AI products, applications, and solutions tailored to specific business needs. Provide implementation guidance throughout the delivery process.
- AI Implementation. Customize and implement Generative AI models, algorithms, and methodologies to enhance product quality and system performance.
- Performance Analysis. Evaluate and analyze the performance of Gen AI systems, offering design recommendations for continuous improvement.
- Cost Estimation. Estimate deployment efforts and costs associated with using LLMs across various business use cases. Develop cost models for different usage patterns.
- Technology Selection. Analyze and make informed technological choices for Generative AI solutions, ensuring alignment with business objectives and industry best practices.
- Component Design. Prototype and design reusable components for LLM-based solution patterns, promoting scalability and efficiency.
- Responsible AI & Security. Architect components of LLM solutions to address Responsible AI and Security considerations, ensuring compliance and integrity.
- Operationalization. Design LLM Ops solutions for large-scale operational deployment, optimizing performance and reliability.
- Collaboration. Collaborate seamlessly with cross-functional teams to identify and prioritize requirements, ensuring alignment with stakeholder expectations.
- Documentation. Create and maintain comprehensive technical documentation, facilitating understanding, troubleshooting, and future development of LLMs.
- Transformer Architecture. Harness the transformative capabilities of transformer architectures in deep learning and NLP to optimize LLM performance and efficiency.
What You Need
- Experience. Minimum 6 years of experience in designing and deploying AI/ML solutions using at least one cloud vendor. Minimum 1 year of specific experience in the LLM and Generative AI space.
- Technical Expertise. Strong background (minimum 6 years) in engineering, machine learning, deep learning, and NLP solutions. Proficiency in cloud environments and familiarity with transformer architectures.
- Education. Bachelor’s degree or equivalent work experience (minimum of 12 years), or an associate degree with a minimum of 6 years of equivalent work experience.
Compensation and Benefits
Accenture offers competitive compensation packages that vary by location, role, skills, and experience. Benefits include comprehensive health coverage, retirement plans, and opportunities for professional development.
Diversity and Inclusion
Accenture is committed to fostering diversity and inclusion, ensuring every individual feels valued within our organization. Our diverse workforce drives innovation and creativity, enabling us to better serve clients and communities worldwide.
Equal Opportunity Employer
Accenture does not discriminate based on age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions are made without regard to protected characteristics under applicable law.
Accommodation
Accenture provides reasonable accommodations for individuals with disabilities or religious observances during the recruitment process and beyond, ensuring equal opportunities for all.
Apply Now
If you're ready to pioneer AI and LLM architectures, pushing the boundaries of technology to reshape industries, apply now to join Accenture as an AI / LLM Architect. Your expertise will drive transformative AI solutions and define the future of data-driven innovation.