# Senior AI/ML Engineer - R01572485 at Brillio

Senior AI/ML Engineer - R01572485 at Brillio in Bangalore, Karnataka, India. Hybrid. Posted October 8, 2026.

- Company: Brillio
- Location: Bangalore, Karnataka, India
- Workplace: Hybrid
- Experience: 6+ years
- Posted: 2026-10-08
- Apply: https://jobs.lever.co/brillio-2/8dc75ccf-ce5b-474e-b806-9c5082c85f9c/apply
- Source: https://jobmagic.ai/jobs/senior-aiml-engineer-r01572485-brillio-t7ggc2

## 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

## Description

**Senior AI/ML Engineer**

### Job requirements

**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:**

- 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

**Required Skills:**

- 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

**Preferred Skills:**

- 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

**Desired Qualifications:**

- 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)