Frontline AI Engineer

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.
Frontline AI Engineer II

Primary Skills

• Sagemaker Studio, Vertex AI, Data Robot, SageMaker, Privacy (Federated Learning, Privacy preserving Algorithms), Model Provisioning: Kubernetes, Kibana, Databricks ML, Model Monitoring, Explainability (SHAPE, LIME, SHAPLEY), Azure ML, Bias Detection/Correction in Data, Big Query ML, Azure Synapse ML, Deployment Strategies (A/B, Blue green, Canary), Model testing, Integration testing, Domino Datalabs, Model Experimentation

Job requirements

Experience Range: with at least 12 years of experience in software engineering, solution development, data/AI engineering, cloud technologies, and enterprise technology delivery

Key Responsibilities:
  1. Lead collaboration with business and technology stakeholders to analyze complex business problems, workflows, and requirements, translating them into actionable technical solutions with measurable impact
  2. Architect, design, develop, test, and deploy production-grade software applications, APIs, services, data pipelines, and AI/ML solutions using industry-standard tools and frameworks
  3. Build rapid prototypes and proof-of-concepts to validate technical approaches and demonstrate business value, iterating based on stakeholder feedback
  4. Integrate developed solutions with enterprise applications, data platforms, APIs, cloud services, and third-party systems, ensuring seamless interoperability and performance
  5. Implement robust testing, monitoring, logging, observability, security, and performance practices to ensure reliability, scalability, and compliance of deployed solutions
  6. Establish and maintain CI/CD pipelines, automation workflows, and deployment strategies such as A/B, blue-green, and canary deployments in collaboration with DevOps and platform teams   7. Leverage AI and GenAI capabilities to develop intelligent applications, automation tools, and data-driven solutions, ensuring explainability and bias mitigation in models   8. Document solution architecture, technical designs, implementation decisions, APIs, and operational procedures, ensuring clarity and maintainability for future enhancements