Solution Architect – GenAI

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Job Description

As a Solution Architect specializing in Generative AI (GenAI), you will play a pivotal role in designing, developing, and implementing advanced AI solutions that leverage generative models to solve complex business challenges. You will work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to architect scalable and efficient AI-driven applications. A key part of your role will involve migrating legacy applications into a strategic, modern architecture by integrating GenAI technologies. Additionally, you will leverage GenAI for enhancing software testing processes, ensuring robust and reliable applications. 

Responsibilities

• Architectural Design: Lead the design and architecture of GenAI solutions, ensuring they are scalable, robust, and align with business goals. 
• Legacy Migration: Assess legacy applications and design a roadmap for their migration to a strategic architecture leveraging GenAI, ensuring minimal disruption and optimal performance. 
• Software Testing: Utilize GenAI to develop innovative testing frameworks and tools that enhance the efficiency and effectiveness of software testing processes. 
• Technical Leadership: Provide technical leadership and guidance in the development and deployment of generative AI models, including natural language processing (NLP), image generation, and other related domains. 
• Solution Development: Collaborate with engineers to develop and implement AI models, ensuring they are integrated seamlessly into the existing technology stack. 
• Stakeholder Collaboration: Work closely with business stakeholders to understand requirements, translate them into technical specifications, and ensure solutions meet business needs. 
• Innovation and Research: Stay abreast of the latest advancements in generative AI and related technologies, identifying opportunities for innovation and improvement within the organization. 
• Performance Optimization: Optimize the performance of GenAI solutions, including model training, inference, and scalability. 
• Risk Management: Identify potential risks associated with AI solutions, including ethical considerations, and develop strategies to mitigate these risks. 
• Documentation: Maintain comprehensive documentation of architecture, design decisions, and processes to ensure knowledge sharing and continuity. 

Requirements

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field. 

• Experience: 
  • Proven and demonstrable experience in AI/ML development and solution architecture. 
  • Proven experience with generative AI models (e.g., GPT, DALL-E, Stable Diffusion) and frameworks (e.g., TensorFlow, PyTorch). 
  • Experience in migrating legacy applications to modern architectures. 
  • Experience in leveraging AI for software testing and quality assurance. 
  • Building and deploying large-scale AI systems in production environments. 
  • Working with large datasets and big data technologies. 
  • Implementing AI ethics and governance frameworks. 

• Technical Skills: 
  • Strong programming skills in languages such as Python, Java, or C++. 
  • Proficiency in AI/ML frameworks and tools. 
  • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes). 
  • Knowledge of data engineering, including ETL processes, data lakes, and data warehousing.