Designation : AI Cloud Stack Architect

Experience : 15+ years

Location : Bangalore (Hybrid)

Key Responsibilities :

Cloud Stack & Platform Architecture :

- Architect and design scalable, secure, and high-performance cloud-native platforms and infrastructure solutions.

- Build and optimize cloud stack architectures across public, private, and hybrid cloud environments.

- Design distributed systems leveraging Kubernetes, microservices, and event-driven architectures.

- Drive architectural decisions, technical roadmaps, and platform integration strategies.

- Ensure solutions meet scalability, reliability, performance, and cost optimization objectives.

AI, GenAI & Agentic AI Integration:

- Design and integrate AI/ML-powered capabilities into cloud platforms and infrastructure products.

- Build AI-powered tools to improve engineering productivity, operations, observability, support, and customer experience.

- Leverage Generative AI, Agentic AI, and LLMs to automate workflows, troubleshooting, capacity planning, root cause analysis, and intelligent operations.

- Develop enterprise AI solutions from requirement gathering and prototyping through productization and large-scale deployment.

- Apply AI/ML, NLP, Deep Learning, and Computer Vision techniques to solve complex infrastructure and cloud engineering challenges.

Product Engineering & Innovation:

- Collaborate with Product, R&D, Engineering, and Architecture teams to identify AI-driven opportunities that enhance product capabilities and operational efficiency.

- Develop reusable architecture patterns, governance frameworks, and integration standards.

- Design intelligent automation frameworks for cloud operations and platform management.

- Mentor teams on architecture best practices, cloud-native engineering, and AI adoption strategies.

- Align technology initiatives with business objectives, growth strategies, and customer needs.

Mandatory Skills:

- 15+ years of overall experience with at least 5+ years in Cloud Architecture roles.

- Strong background in Product Engineering, System Design, and Enterprise Architecture.

- Hands-on experience with Cloud Platforms (AWS, Azure, GCP) and hybrid cloud environments.

- Expertise in Kubernetes, containerization, microservices, and distributed systems.

- Strong knowledge of Elasticsearch, observability platforms, and cloud-native technologies.

- Strong expertise in AI/ML algorithms, Deep Learning, NLP, and Computer Vision.

- Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and related ecosystems.

- Experience designing and implementing Generative AI, Agentic AI, and LLM-powered solutions.

- Strong programming skills in Python and experience debugging distributed and system-level environments.

- Deep understanding of software development methodologies, cloud-native architectures, and enterprise integration patterns.

- Excellent analytical, problem-solving, and performance optimization skills.