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.

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. Solid 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.

📌 Associate Principal - Architecture ( Lead AI/ML Solution Architect ) (Bengaluru)
🏢 Vivantify Technology Solutions India
📍 Bengaluru