Lead Full Stack Engineer

Responsibilities:

• Architect and Execute: Lead the design of end-to-end features, from high-performance React-based interfaces to scalable Java/Python microservices.
• AI Innovation: Drive the integration of LLMs and AI agents into the New Relic ecosystem, including building and maintaining MCP (Model Context Protocol) servers to bridge our data with AI models.
• Scale Heavily: Build and maintain highly available, multi-threaded backend services that handle massive data throughput and concurrency.
• Technical Leadership: Act as a force multiplier. You'll lead system architecture discussions, conduct deep-dive code reviews, and set the standard for engineering excellence.
• Collaborate: Partner closely with Product and Design to translate complex data visualizations into intuitive, performant user experiences.
• Mentor: Foster a culture of growth by guiding junior and senior engineers through complex technical hurdles.

Requirements:

• Experience: 8+ years of professional software development experience, with a proven track record in a lead or staff capacity.
• Frontend Proficiency: Proficiency in React (preferred) or Angular/UI framework, with a focus on state management, performance optimization, and data visualization.
• Backend Depth: Expert-level knowledge of Java or Python. You should be comfortable with multi-threading, concurrency patterns, and asynchronous programming.
• Add API Design and Integration: Explicitly state experience in designing, building, and consuming secure, performant RESTful APIs or GraphQL.
• Distributed Systems: Extensive experience designing and scaling distributed architectures that operate under high load.
• AI/ML Familiarity: Experience working with LLM APIs, prompt engineering, or building MCP servers to enable AI-driven workflows.
• Leadership: Experience leading cross-functional projects and mentoring mid-to-senior-level engineers.

Nice-to-haves:

• Experience with front-end technologies (HTML, JavaScript, CSS, Angular, React).
• Experience with Go or other high-concurrency languages.
• Knowledge of Big Data technologies (Kafka, ClickHouse, or Spark).
• Familiarity with Kubernetes, Docker, and modern CI/CD pipelines.
• Contributions to open-source projects or the AI/MCP community.