Associate Principal - Architecture ( Lead AI/ML Solution Architect )

Location: Bengaluru
Experience: 12–16 Years
Employment Type: Permanent
Openings: 1
About The Role
We are seeking an experienced Lead AI/ML Solution Architect with 12+ years of experience designing, developing, and deploying enterprise-scale AI/ML solutions across cloud and edge environments. The role focuses on Azure Cloud Architecture, MLOps, Computer Vision, Edge AI, Data Architecture, and API Integration. The ideal candidate will combine solution architecture expertise with hands-on technical experience to take AI/ML solutions from proof of concept to production and enterprise scale.
Job Description
The Lead AI/ML Solution Architect will design secure, scalable, resilient, and production-ready AI/ML architectures that address complex business and operational challenges. The candidate will define end-to-end architectures covering data ingestion, processing, feature engineering, model training, inference, application integration, monitoring, and governance.
The role involves developing computer vision and edge AI solutions, designing hybrid cloud and edge architectures, and establishing enterprise-grade MLOps practices. The architect will leverage Microsoft Azure, Python, Docker, Kubernetes, and CI/CD to build and operationalize scalable AI/ML platforms.
The candidate will also lead data, API, microservices, application, security, and governance architecture initiatives. Strong technical leadership is essential to guide engineering teams, conduct architecture reviews, mentor developers, and collaborate with business stakeholders to deliver reliable AI/ML solutions at scale.
Key Responsibilities
AI/ML Solution Architecture: Define end-to-end architectures for machine learning, deep learning, predictive analytics, and Generative AI solutions.
Computer Vision and Edge AI: Design real-time video and image analytics solutions using technologies such as YOLO, OpenCV, CNNs, and Transformer-based models.
Azure Cloud Architecture: Design secure, highly available, scalable, and cost-efficient cloud and hybrid cloud-edge architectures.
MLOps and Lifecycle Management: Establish model versioning, experiment tracking, model registries, monitoring, automated retraining, and lifecycle management.
Data Architecture: Design batch and real-time data pipelines supporting structured, semi-structured, and unstructured data.
API and Integration Architecture: Develop RESTful API, event-driven, and microservices-based integration architectures for enterprise applications and IoT/OT platforms.
Application and Platform Architecture: Define cloud-native application patterns, containerized workloads, caching, messaging, database, and service-discovery strategies.
Security and Governance: Incorporate security by design, data protection, encryption, responsible AI, model security, and auditability.
Productionization and Scalability: Evaluate proof-of-concept solutions, identify production-readiness gaps, define SLAs/SLOs, and optimize infrastructure and inference costs.
Technical Leadership: Lead architecture reviews, mentor engineering teams, prepare architecture documentation, and support technical proposals and solution demonstrations.
Required Skills
AI/ML Solution Architecture
Machine Learning and Deep Learning
Computer Vision and Predictive Analytics
Generative AI and LLM Architecture
Microsoft Azure Cloud Architecture
MLOps and AI Lifecycle Management
Python Development
Docker and Kubernetes
Git, CI/CD, and Infrastructure as Code
YOLO, OpenCV, PyTorch, and TensorFlow
Object Detection, Image Classification, Object Tracking, and Segmentation
Video Analytics, Edge Inference, and GPU Optimization
Data Engineering and Data Architecture
RESTful APIs, Microservices, and Event-Driven Architecture
Azure API Management and Cloud Security
Productionization and Enterprise-Scale AI/ML Solutions
Mandatory Skills
Industrial AI – Machine Learning (ML)
Preferred Skills And Qualifications
Experience in Oil & Gas, Energy, Manufacturing, Utilities, Mining, or other industrial environments.
Exposure to Industrial IoT (Azure IoT), Operational Technology (OT), and Edge AI.
Experience deploying AI/ML solutions across cloud and edge environments.
Strong understanding of enterprise architecture standards, technical design reviews, and production deployment practices.
Candidate Profile
The ideal candidate should have a strong combination of solution architecture expertise and hands-on AI/ML engineering experience. They should be capable of translating business requirements into scalable architectures, guiding multidisciplinary engineering teams, and taking AI/ML solutions from proof of concept to enterprise production. Excellent communication, stakeholder management, and technical leadership skills are essential.
Benefits Package
Competitive salary and benefits package.
Opportunities for professional growth and development.
A collaborative and inclusive work environment.
The opportunity to work on exciting and challenging projects with leading clients.

Work arrangement
No