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.
- Solid 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.

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