About the role

Application Reliability Engineer – Data & AI

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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

Skills & Tags

ai data

Aplyr's read

Michelin excels in tire innovation and sustainable mobility, attracting professionals passionate about cutting-edge technology and environmental responsibility.
Synthesized from recent postings & public sources

What's promising

•Michelin is a leader in tire technology innovation, consistently pushing industry boundaries.
•The company is deeply committed to sustainability, aligning with global environmental goals.
•Michelin offers diverse career opportunities across various global locations and functions.

What to watch

•The tire industry faces volatility due to fluctuating raw material prices.
•Adapting to rapid changes in automotive technology can be challenging.
•Global operations may lead to complex logistical and regulatory hurdles.

Why Michelin

•Michelin's dedication to sustainable mobility sets it apart in the automotive sector.
•The company has a strong focus on research and development in tire technology.
•Michelin's global presence provides employees with international career opportunities.

Aplyr’s read is generated by AI from public sources. Was it useful?