Senior AI/ML Engineer - R01572485

Brillio 2; Bengaluru; On-site; INR 300,000 - 560,000; Full time

Job summary

Brillio 2 Bengaluru seeks Senior AI/ML Engineer to lead design and architecture of enterprise-scale AI platforms, ensuring scalability, security, and operational readiness.

The role requires hands-on experience in model lifecycle management, MLOps/LLMOps, AI observability, and governance, with collaboration across business, data, and platform teams to deliver production-ready AI capabilities.

Qualifications

• 6+ years of experience in AI/ML engineering
• Hands-on design, build, and operationalize enterprise-scale AI platforms
• Experience with model lifecycle management and MLOps/LLMOps
• Knowledge of Responsible AI, governance, and AI security/compliance
• Experience with AI observability and governance tools
• Experience with GenAI architectures and large language models
• Strong programming skills in Python and PySpark
• Experience with cloud-based AI platforms and modern data/AI architectures
• Hands-on experience with ML pipeline orchestration frameworks

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

Skills

AI platform design

MLOps/LLMOps

Python

PySpark

Cloud platforms

AI governance

KubeFlow

BentoML

Decision trees

SVM

Education

Bachelor's degree in CS/Data Science/Math

Tools

TensorFlow

PyTorch

Sci-kit Learn

CNTK

Job description

Senior AI/ML Engineer

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)