Large Language Model Architect
BengaluruFull-timePosted Jul 30, 2026
Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Google Cloud Data Services
Good to have skills : Snowflake Data Warehouse, Microsoft Azure Data Services
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
AI Powered Tech Talent
As a senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
Develop and implement machine learning algorithms, models, and computational systems design and build scalable data pipelines to support model training and production with DevOps & MLOps
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools
Justify the value of model approaches in business problems
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production
Bachelor's Degree or equivalent
Minimum of 7 years of experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.
Minimum of 7 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming
Minimum of 5 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks
Minimum of 4 years of experience in building and deploying AI/ML based software to a cloud environment.
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.
Experience with the following programming languages: Python, C++, Java, R, SQL
Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders
Strong client-facing skillsets in a consulting environment
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation
MS or PhD in related field preferred (computer science, engineering, etc.)
As a Large Language Model Architect, a typical day involves designing and structuring advanced language models capable of understanding and generating human-like text. This role requires careful planning of neural network configurations and managing extensive datasets to ensure the models perform effectively. Collaboration with various teams to align architectural decisions with project goals and continuous refinement of model parameters to enhance natural language processing capabilities are key aspects of the daily workflow.
Roles & Responsibilities:
- Expected to be a SME with deep knowledge and experience.
- Should have influencing and Advisory skills.
- Engage with multiple teams and responsible for team decisions.
- Expected to provide solutions to problems that apply across multiple teams, and provide solutions to business area problems.
- Lead the development and implementation of scalable language model architectures that meet organizational needs.
- Facilitate knowledge sharing and mentorship within the team to foster professional growth and innovation.
- Collaborate with stakeholders to translate business requirements into technical solutions that leverage large language models.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Google Cloud Data Services.
- Good To Have Skills: Experience with Snowflake Data Warehouse, Microsoft Azure Data Services.
- Strong expertise in designing and optimizing neural network architectures for natural language processing.
- Experience in managing and processing large-scale unlabeled text datasets for model training.
- Ability to integrate cloud-based data services to support model deployment and scalability.
- Familiarity with data pipeline development and orchestration in cloud environments.
Additional Information:
- The candidate should have minimum 18 years of experience in Google Cloud Data Services.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Google Cloud Data Services
Good to have skills : Snowflake Data Warehouse, Microsoft Azure Data Services
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
AI Powered Tech Talent
As a senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
Develop and implement machine learning algorithms, models, and computational systems design and build scalable data pipelines to support model training and production with DevOps & MLOps
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools
Justify the value of model approaches in business problems
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production
Bachelor's Degree or equivalent
Minimum of 7 years of experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.
Minimum of 7 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming
Minimum of 5 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks
Minimum of 4 years of experience in building and deploying AI/ML based software to a cloud environment.
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.
Experience with the following programming languages: Python, C++, Java, R, SQL
Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders
Strong client-facing skillsets in a consulting environment
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation
MS or PhD in related field preferred (computer science, engineering, etc.)
As a Large Language Model Architect, a typical day involves designing and structuring advanced language models capable of understanding and generating human-like text. This role requires careful planning of neural network configurations and managing extensive datasets to ensure the models perform effectively. Collaboration with various teams to align architectural decisions with project goals and continuous refinement of model parameters to enhance natural language processing capabilities are key aspects of the daily workflow.
Roles & Responsibilities:
- Expected to be a SME with deep knowledge and experience.
- Should have influencing and Advisory skills.
- Engage with multiple teams and responsible for team decisions.
- Expected to provide solutions to problems that apply across multiple teams, and provide solutions to business area problems.
- Lead the development and implementation of scalable language model architectures that meet organizational needs.
- Facilitate knowledge sharing and mentorship within the team to foster professional growth and innovation.
- Collaborate with stakeholders to translate business requirements into technical solutions that leverage large language models.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Google Cloud Data Services.
- Good To Have Skills: Experience with Snowflake Data Warehouse, Microsoft Azure Data Services.
- Strong expertise in designing and optimizing neural network architectures for natural language processing.
- Experience in managing and processing large-scale unlabeled text datasets for model training.
- Ability to integrate cloud-based data services to support model deployment and scalability.
- Familiarity with data pipeline development and orchestration in cloud environments.
Additional Information:
- The candidate should have minimum 18 years of experience in Google Cloud Data Services.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
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