Senior Software Engineer -alerts

New Relic New Relic · Enterprise · OR · AIOps

Senior Software Engineer role focused on backend services for New Relic's alerting platform, which is part of an AI-first observability solution. The role involves designing, developing, and deploying high-throughput Java/Kotlin services that ingest, persist, and retrieve signal data. A bonus section explicitly mentions hands-on experience with LLMs, AI agents, RAG, and evaluating model output quality, indicating AI/ML is a significant, albeit bonus, aspect of the role's future direction and customer-facing product.

What you'd actually do

  1. Design, develop, and deploy backend services in Java/Kotlin that process high-volume telemetry and alerting workloads, with reliability and customer impact top of mind
  2. Collaborate with product managers and engineers who specialize in high-throughput data streaming systems, computing infrastructure, design, UIs, and customer-facing APIs
  3. Implement exciting new Alerting features that affect our entire pipeline, and also help reduce tech debt and retire old architecture
  4. Advocate for architecture improvements, provide future direction, and clearly articulate reasons why while assessing tradeoffs
  5. Develop and deploy your code to customers multiple times per day

Skills

Required

  • 5+ years of professional backend software engineering experience
  • SaaS or product-based environment experience
  • Strong proficiency in Java (Kotlin preferred, willingness acceptable)
  • Solid grasp of OOP principles
  • Solid grasp of RESTful APIs
  • Solid grasp of multi-threaded programming
  • Experience building multi-threaded Java services
  • Experience shipping reliable high-throughput services to customers in a production environment
  • Experience with relational databases: complex SQL, optimization, pagination, partitioning, and scaling
  • Experience working with distributed systems
  • Experience delivering APIs consumed by internal and/or external customers
  • Demonstrated empathy for the end user
  • Experience working in an agile environment characterized by rapid change
  • Strong interpersonal skills
  • Ability to seek consensus
  • Ability to lead by example
  • Persistence and tenacity

Nice to have

  • Hands-on experience building with LLMs and AI agents
  • Designing prompts
  • Integrating LLM APIs
  • Building retrieval-augmented workflows
  • Evaluating model output quality
  • Developing/maintaining MCP (Model Context Protocol) servers
  • Familiarity with message queuing systems
  • Familiarity with streaming patterns like Kafka
  • Familiarity with Flink
  • Familiarity with Spark Streaming
  • Familiarity with AMQP (RabbitMQ)
  • Familiarity with gRPC
  • Familiarity with Kubernetes
  • Familiarity with Docker
  • Familiarity with Terraform
  • Cloud computing experience (AWS, GCP, or Azure)
  • Frontend awareness or working knowledge (React, TypeScript, GraphQL, CSS)

What the JD emphasized

  • reliability and customer impact top of mind
  • high-volume telemetry and alerting workloads
  • high-throughput data streaming systems
  • high-throughput pipelines
  • shipping reliable high-throughput services to customers in a production environment
  • distributed systems and an understanding of how to write code and queries that perform at scale
  • data logistics, persistence, and retrieval at scale

Other signals

  • AI-first world
  • intelligent platform
  • AI agents
  • LLMs
  • retrieval-augmented workflows
  • model output quality
  • observability