Distinguished IT Software Engineer

Your CareerAs a Distinguished Architect for Enterprise AI Platform, you will be driving the design, implementation, scaling, and evangelism of the end-to-end platform that will be used across IT  and Enterprise business functions (Sales, Marketing, Finance, HR, Legal, etc).Distinguished Enterprise Architect to lead our transformation toward AI-first development practices while optimizing developer productivity and modernizing our enterprise application landscape.We are looking for a visionary leader who will architect and drive the implementation of cutting-edge developer productivity solutions and a modern enterprise applications landscape with AI at the core. This role bridges the gap between emerging AI technologies and practical enterprise needs while establishing architectural standards that accelerate delivery velocity across the organization.The Distinguished Architect will ensure that all transformation efforts are strategically aligned, scalable, reusable, and sustainable.This role directly impacts the organization's ability to innovate faster, reduce time-to-market, and maintain engineering excellence while scaling AI capabilities across all business functions.Your ImpactVision & Design: Define and evangelize enterprise-wide architectural vision for engineering excellence, developer productivity platforms, and AI-integrated applications.Engg Excellence: Establish architectural principles, design patterns, and engineering standards that prioritize quality, reliability, maintainability, and AI-first approaches.Drive technical strategy for internal developer platforms (IDPs), code quality frameworks, development toolchains, reducing tech debt and improving delivery velocity. Design and implement comprehensive code quality frameworks including automated testing, static analysis, and security scanning. Architect self-service capabilities, automated testing frameworks, and deployment pipelines with built-in quality gates.Technology & Platforms: Champion platform engineering practices, infrastructure-as-code methodologies, and shift-left quality approaches.Drive selection of AI tools, frameworks, cloud solutions, and hybrid infrastructure that align with business and engineering needs.Governance: Establish metrics and observability systems to measure and continuously improve both developer productivity, code quality and improve security posture. Promote adoption of a consistent technology stack reducing complexity. Lead the integration of AI/ML capabilities into enterprise applications and development workflows.Cross functional leadership: Collaborate with engineering leadership to align architectural decisions with business objectives and quality standards. Foster a culture of continuous learning, technical excellence, and engineering craftsmanship. Innovation Leadership: Actively learn and incorporate advances in AI, GenAI, LLMs, AIOps, and scalable architectures. Bring emerging innovations into production through POCs, hackathons, and controlled experimentation.