Job Duties and Responsibilities:

• Evaluate current software release and testing workflows to identify opportunities for AI-driven automation and intelligent diagnostics.
• Collaborate with cross-functional teams to understand and analyze business requirements, identifying gaps and aligning technical solutions with business objectives.
• Lead the product automation and DevOps roadmap, defining milestones, ensuring progress through code reviews, and enabling flawless product delivery.
• Orchestrate deployment of new features and service updates in a Microservices environment, ensuring seamless integration across scalable Cloud infrastructure
• Implement and monitor Continuous Integration/Continuous Deployment (CI/CD) pipelines using tools such as Jenkins or GitLab to ensure consistent delivery of code across environments.
• Mentor and guide junior engineers in best practices and engineering principles to drive team productivity and software quality.
• Utilize Test-Driven Development (TDD) methodologies to ensure rigorous testing, leading to a reduction in post-production defects.
• Implement monitoring systems and proactive issue detection to reduce high-priority incidents by 50%, ensuring operational stability.
• Support the creation of architectural diagrams and design specifications to aid automation.
• Develop, deploy and maintain containerized applications using Docker and Kubernetes, integrating with Helm and Terraform for scalability.
• Collaborate with AI/ML and software engineering teams to automate tasks such as documentation, test data generation, and release analysis.
• Create detailed technical documentation, standard operating procedures and team onboarding guides.
• Design and manage Cloud-based Testbed infrastructure to enable global access, parallel CI, and cross-team reuse.

Technologies & Tools involved:

• CI/CD & Version Control: Jenkins, GitHub, GitLab
• Programming & Scripting: Python, Shell/Bash (Java or Go a plus)
• Automation & Frameworks: PyTest, Robot Framework, Cypress, Selenium
• AI & LLM Integration: Custom GPTs, Custom Agents, RAG frameworks, Vector DBs
• Containerization & Orchestration: Docker, Kubernetes, Terraform, Helm
• Monitoring & Logging: New Relic, Prometheus, Grafana, ELK Stack
• Databases: SQL and NoSQL (Elasticsearch, MongoDB is a plus)
• Virtualization: VMware, VirtualBox
• Operating Systems: Linux, Unix, Windows