AI LLM Technology Architecture Manager

 About The Role  

Skill required: Tech for Operations - Technology Architecture

Designation: AI LLM Technology Architecture Manager

Qualifications:Any Graduation

Years of Experience:13 to 18 years
Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song"” all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com
What would you do? You will be part of the Technology for Operations team that acts as a trusted advisor and partner to Accenture Operations. The team provides innovative and secure technologies to help clients build an intelligent operating model, driving exceptional results. We work closely with the sales, offering and delivery teams to identify and build innovative solutions. The Tech For Operations (TFO) team provides innovative and secure technologies to help clients build an intelligent operating model, driving exceptional results. Works closely with the sales, offering and delivery teams to identify and build innovative solutions. Major sub deals include AHO(Application Hosting Operations), ISMT (Infrastructure Management), Intelligent Automation Process of development of methodical information technology specifications, models and guidelines,using a variety of Information Technology notations. Estimating, architecting, implementing, testing, assessing and selling Technology Architectures, including but not limited to all the ADM Technology Architecture work-stream activities and deliverables, covering the required blueprint & roadmap, analysis, design, build, test and deploy phases.

What are we looking for? We are seeking a highly experienced and visionary AI/ML Computational Science Manager to lead the design and implementation of cutting-edge technology architectures for advanced AI/ML solutions, with a strong focus on Agentic AI use case development. This role will bridge the gap between computational science, AI/ML engineering, and technology architecture, driving the development of scalable, robust, and innovative AI-powered systems. Strong programming proficiency in Python or C# with relevant AI/ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, ML.NET). Deep understanding of machine learning algorithms (regression, classification, clustering, deep learning). Experience with data preprocessing, feature engineering, model selection, and hyperparameter tuning. Familiarity with cloud platforms (AWS, Azure, GCP) and their AI/ML services. Strong knowledge of software architecture principles, including microservices and distributed systems. Knowledge of Big Data processing frameworks like Spark or Hadoop. Soft
Skills:

Excellent communication, collaboration, and leadership skills. Ability to translate complex technical concepts into clear and concise language. ? Desired
Qualifications:Experience with MLOps practices (CI/CD for ML models, model monitoring, and deployment). Experience with natural language processing (NLP) or computer vision applications. Experience with Agentic AI concepts.
Roles and Responsibilities:

Architecture Design & StrategyDefine and implement the overarching AI/ML technology architecture, ensuring alignment with business goals and Agentic AI initiatives. Select and evaluate appropriate AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, ML.NET) and cloud platforms (AWS, Azure, GCP) based on project requirements and computational efficiency. Design scalable data pipelines for efficient data ingestion, processing, feature engineering, and model training. Develop and implement model deployment strategies, including cloud-based deployment and edge computing solutions. Establish architectural standards and best practices for AI/ML development. Computational Science & Model OptimizationApply computational science principles to optimize AI/ML models for performance, accuracy, and efficiency. Collaborate with data scientists to translate complex algorithms into efficient software implementations. Develop and implement model monitoring and evaluation strategies to ensure continuous improvement. System Integration & DeploymentOversee the integration of AI/ML models into existing applications and APIs, ensuring seamless data flow and user experience. Design and implement robust monitoring and logging systems to track model performance and identify potential issues. Lead the deployment of AI/ML solutions to production environments, ensuring scalability and reliability. Technical Leadership & MentorshipProvide technical leadership and guidance to the AI/ML development team. Stay abreast of the latest advancements in AI/ML technologies and computational science, and identify opportunities for innovation. Mentor junior developers on AI/ML concepts, implementation techniques, and architectural best practices. Promote MLOps best practices within the team.
 Qualification Any Graduation