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 up-to-date 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 Architecture

Software Engineering

- Full Stack Development
- React
- TypeScript / JavaScript
- Node.js
- API Development
- Microservices Architecture
- Event-Driven Architecture
- Testing Frameworks

DevOps & Automation

- CI/CD Pipelines
- Git
- Infrastructure as Code (IaC)
- Containerization
- Automation Frameworks
- Monitoring & Observability
- Logging & Operational Excellence

Data & 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 Environments

AI & Data Engineering

- MLOps
- AI Platform Engineering
- Model Serving
- Apache Airflow
- Astronomer
- Apache Spark
- Databricks

Domain Experience

- Retail
- eCommerce
- Supply Chain
- Customer-Facing Digital Platforms

Key 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

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