Own fault-management modules end to end, designing and delivering Java and Spring Boot microservices, Kafka-based near-real-time pipelines, and Spark analytics jobs. Responsibilities include distributed-systems design, performance and reliability optimization, AI-assisted development, anomaly-detection integration, production debugging, incident escalation, testing, observability, on-call support, and CI/CD improvements.
Summary:
About the RoleYou'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:
Similar Jobs
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Build and evolve scalable backend products and services, design secure APIs and distributed systems, improve performance and reliability, and lead projects from discovery through rollout. Collaborate with product, frontend, and data teams; contribute to architecture, testing, code reviews, and CI/CD. Address third-party integrations, data synchronization, and event-driven systems while mentoring engineers and advocating for effective backend technologies.
Top Skills:
AWSCi/CdDockerJavaKafkaKotlinKubernetesMicroservicesNoSQLRabbitMQRestful ApisSQL
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Develop full-stack applications using React or Flutter, Python, AWS, microservices, APIs, databases, and CI/CD pipelines. Integrate AI technologies, implement application and data security, manage cloud architecture according to the AWS Well-Architected Framework, and oversee the application lifecycle. Collaborate with cross-functional teams and mentor junior engineers.
Top Skills:
APIsAWSAws Well-Architected FrameworkCi/CdDatabasesFlutterMicroservicesNext.JsPythonReact
Consumer Web • HR Tech
Lead the design and implementation of scalable software systems across Built In’s product lines. Drive technical features, improvements, AI-enabled capabilities, and end-to-end software development on public cloud platforms. Analyze system-level issues, implement solutions, collaborate across product and technology teams, and mentor engineers while promoting agile development, observability, continuous delivery, and engineering excellence.
Top Skills:
.NetAIAWSAzureGCPRazor
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
