Senior Software Engineer

• *Summary:**

About the Role

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.

Tech Stack

Java · Spring Boot · Apache Kafka · Kafka Streams · Kafka Connect · Apache Spark**Duties \& Responsibilities:**

• *Job Description – Senior Software Engineer**

• *Responsibilities**

Module Ownership

• Own one or more fault\-management modules end\-to\-end
• Write LLD documents for every feature request and present for team review
• Drive technical decisions within your module — velocity vs. reliability trade\-offs

Near\-Real\-Time Pipelines

• 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

Backend Engineering

• Build cloud\-native microservices using Java and Spring Boot
• Design idempotent consumers, DLQs, and back\-pressure for exactly\-once / at\-least\-once semantics

Agentic Development

• 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

Debugging \& Incident Support

• Diagnose issues across Kafka brokers, Streams topologies, Spark executors, and Spring Boot services
• Primary escalation point for critical production incidents in your module
• Write runbooks and post\-mortems to prevent repeat incidents

Quality \& Operational Excellence

• Unit, integration, and contract tests; peer code reviews
• Observability — metrics, tracing, structured logging; on\-call rotation
• Contribute to CI/CD and infra\-as\-code improvements

• *Required Skills**

• 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)

• *Good 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, cloud\-native deployments (AWS / Azure / GCP)

• *Pre\-Requisites / Skills / Experience Requirements:**