Project Role : Technology Architect
Project Role Description : Review and integrate all application requirements, including functional, security, integration, performance, quality and operations requirements. Review and integrate the technical architecture requirements. Provide input into final decisions regarding hardware, network products, system software and security.
Must have skills : Data & AI Strategy
Good to have skills : Accenture Benefits Management System
Minimum 15 year(s) of experience is required
Educational Qualification : Bachelors or Masters degree in Computer Science Engineering or a related field

Summary: We are seeking a highly experienced GenAI Architect with over 10 years of experience in architecting multiple GenAI solutions and taking end-to-end delivery ownership. The ideal candidate will have a strong background in cloud architecture and a deep understanding of LLM prompting, tuning, and training. The GenAI Architect will be responsible for engaging with clients, understanding their requirements, and developing solution blueprints to meet their needs. Roles & Responsibilities: - Architecting and designing GenAI solutions based on client requirements and taking ownership of end-to-end delivery of GenAI projects - Engaging with clients to understand their needs and provide tailored solutions, developing solution blueprints and presenting them to clients and providing expertise in cloud architecture and integration with GenAI solutions. - Leading and mentoring a team of GenAI developers and engineers and collaborating with cross-functional teams to ensure successful implementation of GenAI solutions. - Proven track record of taking end-to-end delivery ownership of GenAI projects and strong knowledge of cloud architecture and integration with GenAI solutions. - Deep understanding of LLM prompting, tuning, and training, excellent communication and interpersonal skills, Ability to effectively engage with clients and understand their requirements, strong leadership and mentoring abilities and proactive and innovative mindset with a focus on delivering high-quality solutions - nWe are looking for a GenAI Architect who is passionate about leveraging the latest technologies to deliver innovative and impactful solutions for our clients. - Lead the design, development, and implementation of end-to-end MLOps solutions for clients, including data preparation, feature engineering, model training, and deployment. -Collaborate with cross-functional teams to integrate machine learning models into production systems and ensure scalability, reliability, and performance and Work closely with clients to understand their business requirements, translate them into technical specifications, and provide strategic guidance on MLOps best practices. Professional & Technical Skills: - Deep understanding of LLM prompting, tuning, and training, excellent communication and interpersonal skills, Ability to effectively engage with clients and understand their requirements, strong leadership and mentoring abilities and proactive and innovative mindset with a focus on delivering high-quality solutions - We are looking for a GenAI Architect who is passionate about leveraging the latest technologies to deliver innovative and impactful solutions for our clients. - Utilize advanced data science techniques to analyze, interpret, and visualize complex datasets, and derive actionable insights to drive business value and Mentor and coach junior team members, providing guidance on best practices, industry trends, and emerging technologies in the MLOps space. - Proficiency in at least one or more cloud ML services such as AWS SageMaker, Google Cloud AI Platform, or Microsoft Azure Machine Learning. -Strong programming skills in languages such as Python, R, or Scala, and experience with relevant data science and ML libraries and frameworks. - Proven track record of architecting and implementing MLOps solutions at scale, with a focus on automation, monitoring, and continuous integration/continuous deployment (CI/CD) pipelines. Additional Information: - Minimum of 15 years of hands-on experience in data preparation, data pipeline development, model training, and deployment in a production environment.

Bachelors or Masters degree in Computer Science Engineering or a related field

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