Frontline AI Engineer II - R01572473

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

Required Skills: 1. Advanced proficiency in Python, Java, JavaScript/TypeScript, or C# for enterprise application development 2. Hands-on experience with cloud platforms: Azure, AWS, or GCP 3. Expertise in SageMaker Studio, SageMaker, Vertex AI, and DataRobot for model development and deployment 4. Strong knowledge of privacy-preserving algorithms and federated learning techniques 5. Experience with Kubernetes for model provisioning and container orchestration 6. Proficiency in Databricks ML and Domino Data Lab for model experimentation and management 7. Ability to implement model monitoring, explainability (SHAP, LIME), and bias detection/correction 8. Experience with Azure ML, BigQuery ML, and Azure Synapse ML for scalable data science solutions 9. Skill in developing and executing model testing and integration testing strategies 10. Familiarity with Kibana for monitoring and observability in production environments

Preferred Skills: 1. Experience designing and optimizing deployment strategies (A/B, blue-green, canary deployments) 2. Expertise in developing reusable components, frameworks, accelerators, and technical patterns for enterprise-scale solutions 3. Knowledge of regulatory compliance frameworks in AI and advanced model explainability techniques 4. Experience managing large-scale ML pipelines and model experimentation frameworks 5. Proficiency in integrating solutions with complex third-party systems and enterprise data platforms

Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline 2. Certification in cloud platforms such as Microsoft Azure Solutions Architect, AWS Certified Machine Learning Specialty, or Google Professional Machine Learning Engineer 3. Certification in data science or machine learning such as TensorFlow Developer Certificate or Databricks Certified Data Engineer Associate

Know more about DAE: https://www.brillio.com/services-data-analytics/

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Equal Employment Opportunity Declaration

Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation.

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