Senior Solution Architect – GEN AI

Senior Solution Architect – Generative AI

Responsibilities

• Develop and oversee architectural designs for generative AI models, frameworks, and solutions tailored to business needs
• Design scalable pipelines for integrating and deploying generative AI solutions in alignment with enterprise architecture
• Perform in-depth research to stay current on advancements in generative AI, including GPT, DALL-E, and Stable Diffusion to evaluate their applicability
• Collaborate with stakeholders to assess business requirements and translate them into concrete AI strategies and actionable implementation plans
• Lead the end-to-end development, testing, and deployment of generative AI systems, acting as a technical guide for teams
• Advocate for the adoption of best practices, tools, and frameworks to enhance enterprise AI capabilities
• Create APIs and services to integrate generative AI tools within business workflows or customer-facing platforms
• Work closely with data engineers and scientists to ensure high-quality data preprocessing for AI model training
• Implement responsible AI protocols to address governance, ethical usage, and regulatory compliance
• Identify and mitigate data biases, ensuring data privacy and security concerns are addressed
• Act as a mentor for junior AI developers and other cross-functional team members in understanding generative AI technologies
• Facilitate cross-disciplinary collaboration with data scientists, engineers, product managers, and business stakeholders to drive project success
• Benchmark emerging generative AI tools like OpenAI models, Hugging Face, and custom-built frameworks for potential integration and improvements
• Conduct periodic evaluations of deployed AI systems, recommending adjustments and enhancements for improved operational efficiency
  

Requirements

• 15-23 years of overall IT experience with at least 5+ years of proven experience in AI/ML development or architecture roles
• Background in designing and implementing generative AI solutions, including areas like NLP, computer vision, or code generation
• Familiarity with foundational models such as GPT, BERT, and their customization for enterprise use cases
• Knowledge of AI/ML frameworks/tools such as TensorFlow, PyTorch, or Hugging Face models
• Skills in cloud platforms (AWS, Azure, Google Cloud) and container platforms like Docker or Kubernetes
• Proficiency in Python, R, or similar programming languages for building generative AI solutions
• Understanding of MLOps principles, pipeline orchestration tools (Kubeflow, Airflow), and CI/CD practices
• Expertise in responsible AI governance, ethical frameworks, and compliance with data privacy regulations
• Capability to collaborate with multidisciplinary teams to align AI strategies with organizational goals