Platform Engineer

AI Platform Engineering

Platform Engineer

Position Title: Engineer, Platform Engineering

Function: Technology

Experience: 5–8 Years

Location: Bangalore, India

Reporting: Individual Contributor (No Direct Reports)

Data Platform Engg:

Primary skills - Full stack (React, NodeJs, CI/CD, etc.)

Secondary skills - Data engineering (including some exposure to Snowflake, Databricks or similar data platform), AI/Agentic

The resources are expected to build service layer that could be used by Data Engineers

Role Summary

Client is seeking a highly experienced Engineer, Data Platform to design, build, and operate enterprise-grade platform capabilities supporting Data, Analytics, AI, and Agentic AI workloads. The role will be instrumental in modernizing the organization's Data & AI Platform by enabling scalable, governed, self-service, and AI-ready data capabilities across the enterprise

The successful candidate will contribute to the development of Data Engineering as a Service, Self-Service Analytics, Semantic Layer capabilities, Intelligent Data Products, and Agentic AI enablement. This is a hands-on engineering role requiring strong expertise in AWS cloud technologies, Full Stack Development, Platform Engineering, Microservices Architecture, and modern software development practices.

Key Responsibilities

• Design, develop, and enhance enterprise Data & AI Platform capabilities supporting analytics, AI, Agentic AI, and modern data platform use cases.
• Build platform capabilities that enable Data Engineering as a Service, Data Quality as a Service, data discovery, governance, and standardized data consumption patterns
• Develop semantic layer and self-service analytics capabilities to provide business users, analysts, and AI applications with trusted and governed data access
• Build cloud-native applications, APIs, platform services, automation frameworks, and developer tools to improve productivity across Data Engineering, Analytics, AI, and business teams
• Design and implement reusable platform services, accelerators, SDKs, and engineering frameworks for data ingestion, transformation, orchestration, observability, and platform operations
• Develop secure, scalable, and resilient platform solutions on AWS using microservices, CI/CD, Infrastructure as Code (IaC), automation, and DevOps practices.
• Support data quality, metadata management, lineage, observability, governance, security, privacy, and compliance initiatives
• Enable AI-ready platform architecture through data, metadata, orchestration, semantic retrieval, and integration capabilities required for Agentic AI and intelligent automation.
• Collaborate with Data Engineers, Data Scientists, Platform Engineers, Architects, and business stakeholders to deliver scalable platform capabilities.
• Contribute to platform reliability, performance optimization, operational excellence, incident management, and cloud cost optimization activities.

Primary Skills (Must Have)

Platform Engineering & Cloud

• AWS Cloud
• Cloud-Native Architectures
• Platform Engineering
• Cloud Security & Networking
• Scalability & Reliability Engineering
• Distributed Systems ArchitectureSoftware Engineering
• Full Stack Development
• React
• TypeScript / JavaScript
• Node.js
• API Development
• Microservices Architecture
• Event-Driven Architecture
• Testing FrameworksDevOps & Automation
• CI/CD Pipelines
• Git
• Infrastructure as Code (IaC)
• Containerization
• Automation Frameworks
• Monitoring & Observability
• Logging & Operational ExcellenceData & AI Platforms
• Snowflake
• Kafka
• Data Warehousing
• Data Governance
• Data Quality Management
• Semantic Layer Architecture
• Large Language Models (LLMs)
• Agentic AI
• Model Context Protocol (MCP)
• Retrieval-Augmented Generation (RAG)Secondary Skills (Nice to Have)

Advanced Platform & Data Engineering

• Internal Developer Platforms
• Streaming Platforms
• Data Cataloging
• Data Lineage
• Multi-Cloud EnvironmentsAI & Data Engineering
• MLOps
• AI Platform Engineering
• Model Serving
• Apache Airflow
• Astronomer
• Apache Spark
• DatabricksDomain Experience
• Retail
• eCommerce
• Supply Chain
• Customer-Facing Digital PlatformsKey Competencies
• Strong focus on building scalable, reusable, enterprise-grade Data & AI platform capabilities.
• Strong understanding of data products, semantic layers, data governance, AI governance, and enterprise data enablement.
• Passion for delivering secure, trusted, and high-quality data products supporting analytics and AI.
• Strong engineering mindset focused on automation, standardization, and platform innovation.
• Adaptability to evolving Data, AI, Agentic AI, and cloud technologies.
• Excellent stakeholder management and collaboration skills with the ability to translate business requirements into technology solutions.
• Strong analytical and problem-solving capabilities.Experience & Qualifications

Education

Required

• Bachelor's Degree in Engineering or related discipline.Preferred
• Master's Degree in Computer Science, Information Technology, or related field.Experience
• Proven experience building and operating production-grade enterprise platforms and business-critical applications.
• Strong expertise in designing and implementing cloud-native architectures, APIs, microservices, and distributed systems.
• Hands-on experience developing scalable applications using React, TypeScript/JavaScript, and Node.js.
• Experience building and operating solutions on AWS.
• Experience supporting Data & AI Platform modernization initiatives.
• Experience building reusable platform services, APIs, automation capabilities, and developer tools.
• Strong understanding of platform security, identity management, governance, privacy, and compliance.
• Experience implementing Git, CI/CD, Infrastructure as Code, automated testing, Agile delivery, and DevOps practices.
• Experience supporting observability, reliability, performance optimization, and cloud cost management.
• Retail, eCommerce, or large-scale customer-facing digital platform experience preferred.Ways of Working
• Hands-on contributor responsible for designing, building, and operating platform capabilities.
• Collaborates closely with Data Engineers, Data Scientists, Architects, Platform Engineers, and business stakeholders.
• Focused on delivering reusable, scalable, secure, and governed platform services across the enterprise Data & AI ecosystem.
• Supports self-service analytics, AI enablement, intelligent data products, and enterprise platform modernization initiatives