Senior Software Engineer

Overview

Senior Software Engineer on the Fault Management team, building near-real-time streaming pipelines and intelligent fault-processing capabilities within the AIOps platform. Owns module delivery end-to-end, from low-level design through production support, working with platform architects and PMs.

What you'll do

• Own one or more fault-management modules end-to-end.
• Write LLD documents for every feature request and present them for team review.
• Drive technical decisions within your module, including velocity vs. reliability trade-offs.
• Build event-driven pipelines with Kafka Streams and Kafka Connect for fault ingestion, correlation, and enrichment.
• Implement Spark batch and micro-batch jobs for large-scale fault analytics.
• Meet SLA targets for latency, throughput, and fault tolerance.
• Build cloud-native microservices using Java and Spring Boot.
• Design idempotent consumers, DLQs, and back-pressure for exactly-once / at-least-once semantics.
• Use LLM-assisted coding and AI pair-programming tools to accelerate delivery.
• Integrate ML-powered anomaly detection and RCA into fault workflows.
• Prototype new AI capabilities that improve automated fault resolution rates.
• Diagnose issues across Kafka brokers, Streams topologies, Spark executors, and Spring Boot services.
• Serve as primary escalation point for critical production incidents in your module.
• Write runbooks and post-mortems to prevent repeat incidents.
• Write unit, integration, and contract tests; perform peer code reviews.
• Implement observability: metrics, tracing, and structured logging; participate in on-call rotation.
• Contribute to CI/CD and infra-as-code improvements.

What you'll need

• 6+ years of hands-on backend / data engineering experience.
• Production Kafka systems: topics, partitioning, consumer groups, offset management.
• Kafka Streams DSL and Processor API; stateful and stateless topologies.
• Kafka Connect: source and sink connectors, lifecycle management.
• Apache Spark: Structured Streaming, DataFrames, Spark SQL at scale.
• Java 11+ and Spring Boot 3.x: REST, security, reactive patterns.
• Deep debugging across multi-threaded, distributed JVM systems.
• LLD/HLD documentation; distributed systems principles (CAP theorem, eventual consistency).

Nice to have

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

Details

• Location: Chennai, India.