GenAI Solutions Architect is a technologist with deep domain-specific expertise, able to address advanced concepts and feature design. GenAI solution architects combine technical skills in artificial intelligence and machine learning with business acumen.
Responsibilities
- Responsible for driving the architecture design and implementation of GenAI.
- Design and deliver the Data & AI driven GenAI solutions (Baseline code packages).
- Solution design
- Work closely with our teams in understanding their needs and translating them to AI Data and Security solutions.
- Compare various LLM models and publish the outcome.
- Compare various GenAI cloud services and publish the results.
- Provide expertise as a technical resource to solve complex business issues that translate into use case into a solution design.
- Publish the design to integrate the GenAI solution in existing Applications workflow and data services.
- Analysis the New product features in Generative AI and prepare position paper Impact study .
- Working closely with business and technical teams to help enable new capabilities for Client to develop and deploy GenAI workloads on Azure/AWS/GCP.
- Will have the technical depth and business experience to easily articulate the potential and challenges of GenAI models and applications to engineering teams and leadership teams.
- Requires deep familiarity across the stack – compute infrastructure, ML frameworks, orchestration layers, large models, and frameworks like Lang Chain for developing applications powered by GenAI models, MLOPs, and target use cases in the AWS.
- Guide the implementation team on technical aspects.
- Provides implementation guidelines and ensure industry best practices are followed.
- Focusing on ongoing improvement, conduct an evaluation of tools and methods, including data, algorithms, and software development.
Skills Requirement
- Bachelors/Masters/ PhD in a Science, Technology, Engineering, Mathematics (STEM) or Economics related field of study.
- 8 - 10 years of design, implementation, or consulting in applications and infrastructures experience.
- 5+ years of experience training large models across compute types (e.g., GPUs, custom instances), and developing applications powered by GenAI models.
- Relevant training and/or certifications in AI or a related field.
- Deep hands-on understanding of deep learning and other ML algorithms and infrastructure.
