Cloud & Infrastructure Engineer

Experience: 8-10 years

Location: Pune

Role Overview:
Own the end-to-end technical design and implementation of enterprise-grade AI solutions. The role requires broad technical depth across application, hardware, platform, infrastructure, networking, security, scalability, and customer requirements, with strong leadership and solution-design capabilities.

Key Responsibilities:
Ability to co-work with Agentic AI model, Optimizing processes agnatically [agentic optimizing engineering]

Own end-to-end technical architecture and implementation of AI-based systems

Design solutions across application, hardware, platform, network, infrastructure, and other relevant tiers

Perform capacity planning and build reference architectures

Make architecture and technology decisions and evaluate trade-offs

Coordinate with infrastructure engineers, Field/Deployment Engineers, ML Engineers, CSI/Cluster Administrators, developers, and other technical roles

Collaborate closely with customers to understand business and technical problems and translate them into enterprise-grade solutions

Identify functional and non-functional requirements, including requirements that may not be explicitly stated by the customer

Assess existing technical debt and understand the current environment before designing the target solution

Conduct Proofs of Technology (POTs) and Proofs of Concept (POCs) where technology compatibility or suitability needs to be validated

Evaluate compatibility across multiple technology stacks

Design solutions considering enterprise-grade parameters such as security, scalability, reliability, and other relevant quality attributes

Guide technical teams and provide architectural direction throughout implementation

Must be available for on-call support as needed

Ability to collaborate effectively with Agentic AI models

Capability to optimize repetitive processes and workflows using agentic/autonomous engineering approaches

Required Skills:
Strong enterprise AI solution architecture experience

Broad understanding across AI applications, infrastructure, platforms, hardware, networking, and deployment environments

Strong capacity planning and reference-architecture skills

Experience with POCs/POTs and technology evaluation

Strong understanding of enterprise-grade security, scalability, and reliability requirements

Ability to understand technical debt and existing architecture before proposing changes

Strong customer-facing and stakeholder-management capabilities

Ability to coordinate and technically guide multiple engineering disciplines

Preferred Experience:
Experience leading or coordinating multiple engineering teams

Experience designing enterprise-grade AI platforms and solutions

Exposure to complex customer environments and technology stacks