Frontline AI Engineer II - R01572473

Primary Skills

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: Lead collaboration with business and technology stakeholders to analyze complex business problems, workflows, and requirements, translating them into actionable technical solutions with measurable impact Architect, design, develop, test, and deploy production-grade software applications, APIs, services, data pipelines, and AI/ML solutions using industry-standard tools and frameworks Build rapid prototypes and proof-of-concepts to validate technical approaches and demonstrate business value, iterating based on stakeholder feedback Integrate developed solutions with enterprise applications, data platforms, APIs, cloud services, and third-party systems, ensuring seamless interoperability and performance Implement robust testing, monitoring, logging, observability, security, and performance practices to ensure reliability, scalability, and compliance of deployed solutions 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 Leverage AI and GenAI capabilities to develop intelligent applications, automation tools, and data-driven solutions, ensuring explainability and bias mitigation in models Document solution architecture, technical designs, implementation decisions, APIs, and operational procedures, ensuring clarity and maintainability for future enhancements
• Required Skills: Advanced proficiency in Python, Java, JavaScript/TypeScript, or C# for enterprise application development Hands-on experience with cloud platforms: Azure, AWS, or GCP Expertise in SageMaker Studio, SageMaker, Vertex AI, and DataRobot for model development and deployment Strong knowledge of privacy-preserving algorithms and federated learning techniques Experience with Kubernetes for model provisioning and container orchestration Proficiency in Databricks ML and Domino Data Lab for model experimentation and management Ability to implement model monitoring, explainability (SHAP, LIME), and bias detection/correction Experience with Azure ML, BigQuery ML, and Azure Synapse ML for scalable data science solutions Skill in developing and executing model testing and integration testing strategies Familiarity with Kibana for monitoring and observability in production environments
• Preferred Skills: Experience designing and optimizing deployment strategies (A/B, blue-green, canary deployments) Expertise in developing reusable components, frameworks, accelerators, and technical patterns for enterprise-scale solutions Knowledge of regulatory compliance frameworks in AI and advanced model explainability techniques Experience managing large-scale ML pipelines and model experimentation frameworks Proficiency in integrating solutions with complex third-party systems and enterprise data platforms
• Desired Qualifications: Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline Certification in cloud platforms such as Microsoft Azure Solutions Architect, AWS Certified Machine Learning Specialty, or Google Professional Machine Learning Engineer 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/
• Know what it’s like to work and grow at Brillio: https://www.brillio.com/join-us/
• 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.
• #LI-AY1
• Range: with at least 12 years of experience in software engineering, solution development, data/AI engineering, cloud technologies, and enterprise technology delivery
• Advanced proficiency in Python, Java, JavaScript/TypeScript, or C# for enterprise application development
• Hands-on experience with cloud platforms: Azure, AWS, or GCP
• Expertise in SageMaker Studio, SageMaker, Vertex AI, and DataRobot for model development and deployment
• Strong knowledge of privacy-preserving algorithms and federated learning techniques
• Experience with Kubernetes for model provisioning and container orchestration
• Proficiency in Databricks ML and Domino Data Lab for model experimentation and management
• Ability to implement model monitoring, explainability (SHAP, LIME), and bias detection/correction
• Experience with Azure ML, BigQuery ML, and Azure Synapse ML for scalable data science solutions
• Skill in developing and executing model testing and integration testing strategies
• Familiarity with Kibana for monitoring and observability in production environments
• Lead collaboration with business and technology stakeholders to analyze complex business problems, workflows, and requirements, translating them into actionable technical solutions with measurable impact
• Architect, design, develop, test, and deploy production-grade software applications, APIs, services, data pipelines, and AI/ML solutions using industry-standard tools and frameworks
• Build rapid prototypes and proof-of-concepts to validate technical approaches and demonstrate business value, iterating based on stakeholder feedback
• Integrate developed solutions with enterprise applications, data platforms, APIs, cloud services, and third-party systems, ensuring seamless interoperability and performance
• Implement robust testing, monitoring, logging, observability, security, and performance practices to ensure reliability, scalability, and compliance of deployed solutions
• 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
• Leverage AI and GenAI capabilities to develop intelligent applications, automation tools, and data-driven solutions, ensuring explainability and bias mitigation in models
• Document solution architecture, technical designs, implementation decisions, APIs, and operational procedures, ensuring clarity and maintainability for future enhancements

Additional information

Preferred Qualifications

• Experience designing and optimizing deployment strategies (A/B, blue-green, canary deployments)
• Expertise in developing reusable components, frameworks, accelerators, and technical patterns for enterprise-scale solutions
• Knowledge of regulatory compliance frameworks in AI and advanced model explainability techniques
• Experience managing large-scale ML pipelines and model experimentation frameworks
• Proficiency in integrating solutions with complex third-party systems and enterprise data platforms
• Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline
• Certification in cloud platforms such as Microsoft Azure Solutions Architect, AWS Certified Machine Learning Specialty, or Google Professional Machine Learning Engineer
• 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/
• Know what it’s like to work and grow at Brillio: https://www.brillio.com/join-us/
• 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.
• Additional information
• Know what it’s like to work and grow at Brillio: Click here

Responsibilities

• Lead collaboration with business and technology stakeholders to analyze complex business problems, workflows, and requirements, translating them into actionable technical solutions with measurable impact
• Architect, design, develop, test, and deploy production-grade software applications, APIs, services, data pipelines, and AI/ML solutions using industry-standard tools and frameworks
• Build rapid prototypes and proof-of-concepts to validate technical approaches and demonstrate business value, iterating based on stakeholder feedback
• Integrate developed solutions with enterprise applications, data platforms, APIs, cloud services, and third-party systems, ensuring seamless interoperability and performance
• Implement robust testing, monitoring, logging, observability, security, and performance practices to ensure reliability, scalability, and compliance of deployed solutions
• 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
• Leverage AI and GenAI capabilities to develop intelligent applications, automation tools, and data-driven solutions, ensuring explainability and bias mitigation in models
• Document solution architecture, technical designs, implementation decisions, APIs, and operational procedures, ensuring clarity and maintainability for future enhancements