Platform Engineer

Netcore Cloud Pvt. Ltd.; Bengaluru; Hybrid; INR 1,500,000 - 2,700,000; Full time

Job summary

Netcore Cloud Pvt. Ltd. is seeking an AI-focused Software Engineer to architect and build scalable AI-driven systems for personalization, automation, and predictive insights within our Martech ecosystem.

The role emphasizes data engineering, ML workflows, and distributed systems, with production-grade delivery in cloud environments. You will design high-throughput pipelines, work on real-time processing, and collaborate with cross-functional teams to implement intelligent features that scale

Qualifications

• Strong proficiency in Java, Golang, or Python.
• Hands-on data engineering and ML systems development experience.
• Deep understanding of distributed systems, scalability, and performance tuning.
• Experience with big data frameworks such as Spark, Storm, or Apex.
• Strong foundation in data structures, algorithms, and system design.
• Experience building production-ready systems in cloud environments.

Responsibilities

• Architect and develop scalable, high-throughput data and ML pipelines.
• Design real-time and batch processing systems for large-scale event streams.
• Build production-grade ML workflows and inference systems.
• Optimize distributed systems for performance, reliability and cost efficiency.
• Collaborate with Product, Analytics, and Platform teams to deliver intelligent features.
• Contribute to system design discussions and engineering best practices.

Skills

Java

Golang

Python

Data engineering

Distributed systems

System design

Cloud environments

Big data

Production systems

Tools

Kafka

Hadoop

Hive

Spark Streaming

Spark

Docker

Kubernetes

Kubeflow

Job description

Software Engineer AI

About Netcore UNBXD

Netcore Cloud is a global Martech and Product Discovery leader, enabling brands to deliver intelligent, hyper-personalized customer experiences at scale. Our platform processes billions of events daily, combining advanced data engineering, real-time decisioning, and machine learning to power high-performance SaaS solutions used by thousands of enterprises worldwide.

We operate at the intersection of distributed systems, AI innovation, and large-scale infrastructure - solving complex engineering problems that directly impact global businesses.

The Opportunity

We are looking for a high-impact AI Engineer who thrives in solving large-scale data challenges. You will play a key role in architecting and building intelligent systems that power personalization, automation, and predictive insights across our Martech ecosystem.

This role demands strong engineering fundamentals, system-level thinking, and a deep interest in scalable AI systems.

Key Responsibilities

• Architect and develop scalable, high-throughput Data and ML pipelines.
• Design real-time and batch processing systems for large-scale event streams.
• Build robust, production-grade ML workflows and inference systems.
• Optimize distributed systems for performance, reliability, and cost efficiency.
• Collaborate cross-functionally with Product, Analytics, and Platform teams to deliver intelligent features.
• Contribute to system design discussions and drive engineering best practices.

Core Requirements

• Strong proficiency in Java, Golang, or Python.
• Hands-on experience in data engineering and ML systems development.
• Deep understanding of distributed systems, scalability, and performance tuning.
• Experience with big data frameworks such as Spark, Storm, or Apex.
• Strong foundation in data structures, algorithms, and system design.
• Experience building production-ready systems in cloud environments.

Preferred Qualifications

• Experience with Kafka, Hadoop, Hive, Vertica, or Spark Streaming.
• Exposure to containerization and orchestration tools like Docker and Kubernetes.
• Familiarity with ML lifecycle tools such as Kubeflow or AWS Batch.
• Experience with real-time personalization, recommendation systems, or predictive analytics.

What Makes This Role Exciting

• Work on AI systems operating at massive scale.
• Influence architectural decisions in a rapidly growing SaaS company.
• Solve real-world engineering challenges impacting global enterprises.
• High ownership, high visibility, high growth.