Software Development Engineer 2

Role Overview

You'll be a core individual contributor on the Fault Management team, building near-real-time streaming pipelines and intelligent fault-processing capabilities within our AIOps platform. You own module delivery end-to-end — from low-level design through production support — and work with platform architects and PMs to ship high-impact features.

Responsibilities

• Own one or more fault-management modules end-to-end and write LLD documents.
• Build event-driven pipelines with Kafka Streams and Kafka Connect for fault ingestion and enrichment.
• Implement Apache Spark batch and micro-batch jobs for large-scale fault analytics.
• Build cloud-native microservices using Java and Spring Boot.
• Use LLM-assisted coding and AI pair-programming tools to accelerate delivery.
• Diagnose issues across Kafka brokers, Streams topologies, Spark executors, and Spring Boot services.
• Maintain observability through metrics, tracing, and structured logging.

Requirements

• 3–8 years of hands-on backend / data engineering experience.
• Production Kafka systems experience including topics, partitioning, and consumer groups.
• Proficiency in Kafka Streams DSL and Processor API.
• Experience with Kafka Connect source and sink connectors.
• Expertise in Apache Spark (Structured Streaming, DataFrames, Spark SQL).
• Strong command of Java 11+ and Spring Boot 3.x.
• Deep debugging skills across multi-threaded, distributed JVM systems.
• Knowledge of distributed systems principles like CAP theorem and eventual consistency.

Skills

• Java
• Spring Boot
• Apache Kafka
• Apache Spark
• Kafka Streams

Nice to Have

• AIOps or observability platform experience.
• Agentic development workflows or LLM-integrated toolchains.
• Telecom fault management standards or OSS/BSS domain knowledge.
• Kubernetes, service meshes, or cloud-native deployments (AWS / Azure / GCP).