Principal Software Engineer - Agentic AI

About the role

The Red Hat OpenShift Engineering team is looking for an Agentic AI Quality Lead to join us in Bangalore, India. In this role, you will define the quality and automation strategy at the intersection of Cloud-Native Platforms and Agentic AI. You will lead the transition toward an Agentic SDLC, moving beyond traditional automation to implement Spec-Driven validation and AI-augmented testing workflows. Your mission is to ensure that as we bridge the gap between high-level AI orchestration and low-level Kubernetes primitives of SDLC, building an 'Agentic Platform' that ensures AI-driven software delivery-from automated coding to intelligent testing-maintains the enterprise-grade security and performance expected on OpenShift. You will be responsible for architecting intelligent test frameworks, designing comprehensive validation strategies for both back and front ends, and ensuring that AI-driven prototypes are converted into robust, production-ready system architectures. As an Agentic AI Quality Lead, you will maintain a deep technical mastery of Kubernetes, OpenShift, and distributed systems, while pioneering how we use Agentic tools to drive rapid, reliable software delivery. What will you do: Agentic Quality Governance: Define the evaluation framework for AI agents, specifically focusing on hallucination detection, reasoning accuracy, and non-deterministic outcome validation in OpenShift environments. Security & Compliance of AI Tools: Ensure AI agents used in the SDLC adhere to Red Hat's enterprise-grade security primitives, particularly regarding secure tool-use and data leakage. Lead the research and integration of AI/ML technologies to innovate our quality processes, including automated test generation, predictive defect analysis, and intelligent system diagnostics. Autonomous Test Engineering: Architect "Self-Healing" test suites where AI agents autonomously identify regressions and rewrite test logic based on Spec-Driven changes. Define and oversee the execution of the end-to-end quality strategy for the OpenShift Container Platform, ensuring alignment with product goals and enterprise standards. Architect, design, and lead the development of scalable, intelligent test automation frameworks and infrastructure, empowering developers to test their features efficiently. Govern the failure analysis and bug triage process, analyzing trends to identify systemic quality gaps and driving long-term resolutions. Coordinate with cross component teams to be responsible for bug verification, regression testing. Work with the product release related teams to be responsible for the product delivery related testing. What will you bring: Bachelor's degree or higher, or equivalent in computer science or a related field 10+ years of experience in software quality engineering, with a demonstrated track record in test architecture, strategy, and leadership roles. Evaluation Frameworks: Deep experience with RAG (Retrieval-Augmented Generation) evaluation and benchmarking LLM performance in technical domains (e.g., code generation quality) Experience applying AI/ML concepts to quality engineering challenges, with familiarity in using AI for test optimization, failure prediction, or data analysis. Mastery in designing complex, multi-step prompts for AI agents to predict edge cases in distributed microservices. Expert-level knowledge of designing test strategies for complex, large-scale distributed systems and microservices environments like Kubernetes or Docker. Expert-level programming skills in Go or Java, with proven experience architecting and building large-scale test automation frameworks from the ground up. Proven ability to influence cross-functional teams, including development, product management, and support, to drive a unified vision for product quality. Knowledge of the Linux operating system (any distribution) Solid written and verbal communication skills in English Hands-on with AI Agent to predict edge cases and maintain high coverage across complex distributed systems. Modernization of QA environments utilizing AI-augmented development and spec-driven methodologies to transform the testing lifecycle The following are considered a plus: Knowledge of Amazon Web Services (AWS) EC2, Google Compute Engine (GCE), or Microsoft Azure Knowledge of Linux containers, Kubernetes, Red Hat OpenStack Platform, or Red Hat OpenShift Knowledge of CI/CD and Jenkins - Knowledge of security testing Contributions to open source projects or publicly available code samples Design, develop and maintain automation frameworks and scripts with Ruby, Golang and Python for OpenShift testing and implementation Participate in the test planning and product planning processes Conduct new feature research and design test cases Execute manual and automated tests for OpenShift and deliver clear status in a timely manner. Explore, identify and document new bugs. Advocate for the resolution of bug