AI Solution Architect

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.

Senior Data Science Lead


Primary Skills

• Must-Have

• GenAI expertise
• Solid understanding of classical ML, LLMs
• Experience with NLB, LLMs, and RAC systems (critical)
• Cloud: Azure or AWS (must have experience with one and working knowledge of the other)
• Bidrocks – AWS-based exposure preferred

Specialization

• Data Science Foundation: Data Science Lead

Job requirements

• AI Solution Architect

• AI Architecture Design: Define end-to-end AI/ML architectures and infrastructure, including data pipelines, model training/deployment, inference systems, and monitoring.
• Solution Development: Collaborate with data scientists, engineers, and stakeholders to develop and implement AI/ML models, APIs, and applications.
• Stakeholder Engagement: Translate business requirements into technical solutions and act as a liaison between business and technical teams.
• Technology Evaluation: Evaluate and recommend AI tools, platforms, and frameworks suitable for different use cases (e.g., computer vision, NLP, predictive analytics).
• Security & Compliance: Ensure AI systems comply with data privacy, governance, and security standards.
• Scalability & Performance: Design scalable systems that handle real-time or batch data processing and optimize inference performance.
• Mentorship: Provide technical leadership and guidance to engineers, data scientists, and product teams.
• Documentation: Create architectural blueprints, solution designs, and technical documentation.