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/
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.
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Skills Required
- At least 12 years of experience in software engineering, solution development, data or AI engineering, cloud technologies, and enterprise technology delivery
- Advanced proficiency in Python, Java, JavaScript/TypeScript, or C#
- Hands-on experience with Azure, AWS, or GCP
- Expertise with SageMaker Studio, SageMaker, Vertex AI, and DataRobot
- Knowledge of privacy-preserving algorithms and federated learning
- Experience with Kubernetes for model provisioning and container orchestration
- Proficiency in Databricks ML and Domino Data Lab
- Ability to implement model monitoring, explainability using SHAP or LIME, and bias detection or correction
- Experience with Azure ML, BigQuery ML, and Azure Synapse ML
- Experience developing and executing model testing and integration testing strategies
- Familiarity with Kibana for production monitoring and observability
- Experience designing A/B, blue-green, and canary deployment strategies
- Experience developing reusable components, frameworks, accelerators, and technical patterns for enterprise-scale solutions
- Knowledge of AI regulatory compliance frameworks and advanced model explainability techniques
- Experience managing large-scale ML pipelines and model experimentation frameworks
- Experience integrating solutions with complex third-party systems and enterprise data platforms
- Bachelor's degree in Computer Science, Information Technology, Data Science, or a related discipline
- Cloud certification such as Microsoft Azure Solutions Architect, AWS Certified Machine Learning Specialty, or Google Professional Machine Learning Engineer
- Data science or machine learning certification such as TensorFlow Developer Certificate or Databricks Certified Data Engineer Associate
Brillio Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Brillio and has not been reviewed or approved by Brillio.
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Healthcare Strength — Healthcare is considered comprehensive, including medical coverage for employees and dependents alongside life, disability, and accidental death protections. Feedback suggests these protections are a core strength of the package.
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Leave & Time Off Breadth — Time-off options include paid leave and parental leave, with flexible or ‘flexible PTO’ approaches cited in some contexts. Feedback suggests this breadth helps support work-life balance when team norms permit usage.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings span counseling, financial-management sessions, fitness programs, and travel insurance, plus region-specific extras like discounted IT hardware and work-from-home essentials. Feedback suggests these add-ons enhance perceived value beyond core insurance.
Brillio Insights
What We Do
Brillio is the leader in global digital business transformation, applying technology with a human touch. We help businesses define internal and external transformation objectives, and translate those objectives into actionable market strategies using proprietary technologies. With 2600+ experts and 13 offices worldwide, Brillio is the ideal partner for enterprises that want to quickly increase their core business productivity, and achieve a competitive edge, with the latest digital solutions.






