Application Reliability Engineer – Data & AI

Application Reliability Engineer – Data & AI - - - - - - - - - - - - The Data and AI Application Reliability Engineer you are responsible for owning the post-deployment health, latency, and performance of productionized AI application and Medallion architectures followed for applications. Acting as the problem-solver for technical issues affecting data pipelines, databases, and deployed AI/ML models, ensuring continuous operation and high user satisfaction. Partner with core Feature teams to perform root-cause analysis, optimize PySpark jobs, and reduce system debt Build automated observability dashboards and self-healing mechanisms for automated failure recovery As a part of Job you are required to balance your responsibilities between Proactive Engineering & Automation and Operational Reliability/ Production Health. Key Responsibilities Performance Optimization: Analyze and refactor resource-intensive PySpark jobs, queries, and API endpoints to optimize cost, execution speed, and compute efficiency. Self-Healing Automation : Develop automated recovery routines, DAG rerun triggers, and data quality checks to minimize manual intervention. Engineering Alignment: Partner closely with Feature Teams and Architects to establish strict Definition of Done (DoD) standards and production readiness gates for new deployments. Production Observability & Monitoring: Design, implement, and maintain real-time monitoring and alerting frameworks for Medallion architecture pipelines, feature stores, and AI Applications. Incident Management & Root-Cause Analysis : Lead technical resolution for high-priority production incidents, conducting thorough post-mortems to eliminate recurring failure patterns. Technical Expertise: Azure Data Engineering Stack Proficiency in Databricks , Python, and PySpark. Azure (ADLS Gen2, Azure Data Factory, Key Vault, Azure DevOps) Hands-on experience with Medallion architecture. Cloud and DevOps Fundamentals Understanding of cloud computing concepts and Services, specifically Microsoft Azure. Good handson experience on Python. Good to Have Technical Abilities : Understanding of PowerBI reports will be a plus. DevOps & CI/CD Fundamentals AI & Machine Learning Fundamentals Data Science Fundamentals Generative AI & LLM Fundamentals Behaviour Problem Solver: Ability to reverse-engineering complex system behavior and tracking down bugs. Automation-First: An instinct to automate repetitive tasks . Clear Communicator : Ability to explain technical root causes to non-technical stakeholders clearly. Relevant work experience - 5 yrs