Software Engineer Manager (Database Observability)

About the role

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us!

Your opportunity

At New Relic, we provide our customers real-time insights, so they can innovate faster. Our software delivers insightful observability tools across different technologies and distributed systems, enabling software engineering teams to quickly identify, understand and tackle issues, analyze performance and get the most of their software and infrastructure.

Database Observability is a critical pillar of New Relic's platform strategy. We are looking for an experienced Engineering Manager (M3) to lead a senior, high-performing team building next-generation Database Observability products. Your team will own the entire lifecycle of critical telemetry data flows from lightweight database agents and high-throughput ingestion pipelines to intelligent DB recommendation engines and autonomous DB AI Agents.

You will lead a team that includes senior and Lead-level engineers with deep domain expertise in distributed systems and AI. Your primary value will come from setting strategic technical direction, enabling their best work, and fostering a high-accountability culture while partnering closely with Product and Design to deliver features that directly drive New Relic's Database Observability.

What you'll do

- Manage a full-stack engineering team (6–8 engineers) spanning backend systems, database telemetry, agent engineering, and UI workflows.

- Own end-to-end delivery sprint planning, roadmap execution, system quality, and operational excellence for critical database ingestion and recommendation pipelines.

- Guide the team in harnessing cutting-edge AI technologies including Agentic AI, MCP, and LLMs to evolve database observability from passive monitoring to automated, AI-driven diagnostics and remediation.

- Drive architectural discussions around high-throughput, low-latency ingestion, streaming telemetry (Kafka), and database agent development, holding the team to high engineering excellence standards.

- Partner closely with Product Management and Design to translate high-level vision into actionable, well-engineered execution plans..

- Hire, mentor, and grow engineers at every level. Set clear expectations, manage performance equitably, and build a visible talent pipeline.

- Build a strong DevOps culture where teams own what they ship ensuring robust monitoring, incident response, CI/CD automation, and high reliability.

- Champion modern engineering workflows, including AI-assisted development tools (Claude Code, Cursor, Copilot) to accelerate delivery and spec-driven development.