The Role
Leads the architecture and operationalization of enterprise AI platforms. Establishes MLOps, LLMOps, model lifecycle management, observability, governance, Responsible AI controls, and reusable architecture standards. Collaborates across technical and business teams to deliver production-ready AI capabilities, evaluates emerging technologies, and maintains model governance and documentation. Requires advanced Python and PySpark skills, cloud AI platform experience, statistical modeling expertise, and hands-on KubeFlow, BentoML, Great Expectations, and Evidently AI experience.
Summary Generated by Built In
Senior AI/ML Engineer
Job requirements
- Lead the design and architecture of enterprise-scale AI platforms, ensuring scalability, security, and operational readiness
- Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability to support robust deployment and monitoring
- Establish and enforce Responsible AI principles, governance frameworks, and technical guardrails across AI solutions
- Drive platform-level technical decision-making and define reusable architecture patterns, standards, and reference models for AI and GenAI solutions
- Collaborate with business, data, technology, and platform teams to translate AI architecture principles into production-ready capabilities
- Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms, supporting long-term scalability and business outcomes
- Maintain and improve AI model governance, version control, and documentation for ongoing operational excellence
- Expertise in enterprise-scale AI platform design and operationalization
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
- Advanced programming skills in Python and PySpark
- Experience with cloud-based AI platforms and modern data/AI architectures
- Knowledge of Responsible AI, AI governance, model risk, security, and compliance
- Hands-on experience with KubeFlow and BentoML for ML pipeline orchestration
- Competence in classification algorithms such as decision trees and SVM
- Experience with Great Expectations and Evidently AI for model validation
- Strong proficiency in regression analysis (linear and logistic)
- Statistical analysis and computing for large datasets
- Experience with GenAI architectures, large language models, and AI agents
- Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
- Knowledge of vector databases and AI orchestration
- Understanding of AI observability and Responsible AI frameworks
- Experience developing reusable AI architecture patterns and accelerators
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
- Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate)
- Relevant certification in statistical analysis or advanced analytics (e.g., SAS Certified Specialist, IBM Data Science Professional Certificate)
Experience Range: with at least 6 years of experience in AI/ML engineering, including hands-on expertise in designing, building, and operationalizing enterprise-scale AI platforms Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
Skills Required
- At least 6 years of experience in AI/ML engineering
- Experience designing, building, and operationalizing enterprise-scale AI platforms
- Expertise in enterprise-scale AI platform design and operationalization
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
- Advanced programming skills in Python and PySpark
- Experience with cloud-based AI platforms and modern data/AI architectures
- Knowledge of Responsible AI, AI governance, model risk, security, and compliance
- Hands-on experience with KubeFlow and BentoML
- Competence in classification algorithms, including decision trees and SVM
- Experience with Great Expectations and Evidently AI for model validation
- Strong proficiency in linear and logistic regression analysis
- Statistical analysis and computing for large datasets
- Experience with GenAI architectures, large language models, and AI agents
- Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, scikit-learn, CNTK, Keras, or MXNet
- Knowledge of vector databases and AI orchestration
- Understanding of AI observability and Responsible AI frameworks
- Experience developing reusable AI architecture patterns and accelerators
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related discipline
- Certification in Machine Learning or Data Science
- Certification in statistical analysis or advanced analytics
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.
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The Company
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.
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