Senior Performance Software Engineer

About the Role

Join RelationalAI as a Senior Performance Software Engineer to tackle complex challenges at the intersection of large language models, structured data, and enterprise AI. This is an exciting opportunity to build the observability infrastructure that ensures our breakthrough Superalignment technology delivers trustworthy, high-performance decision intelligence.

Role Impact and Focus

In this role, you will be instrumental in driving a performance-oriented culture across our engineering organization. You will focus on building advanced profiling and observability systems, diagnosing and resolving critical performance bottlenecks across our distributed systems, and contributing to design reviews to ensure performance is a core consideration in all new features.

Key Responsibilities

• Develop and maintain advanced profiling and observability infrastructure using tools like Datadog or Honeycomb.
• Proactively identify, analyze, and resolve performance bottlenecks within complex systems, including distributed computing, database internals, and mathematical optimization solvers.
• Collaborate closely with various engineering teams (including those working on GNNs and GraphRAG) to implement performance improvements.
• Contribute expertise during design reviews to embed performance best practices across the entire engineering lifecycle.

Essential Requirements

• 7+ years of dedicated experience in performance engineering and benchmarking, specifically focused on large-scale data systems.
• Extensive, hands-on experience applying performance engineering methodologies and best practices.
• Expertise in using profiling tools and distributed tracing/observability tools (e.g., Datadog, Honeycomb).
• Deep understanding of distributed computing system architecture, particularly concerning data-intensive applications.
• Proven track record of successfully collaborating with cross-functional engineering teams to achieve customer-centric performance outcomes.

Desirable Skills (Nice-to-Haves)

• Familiarity with Python or Go, as these are the primary languages used by the team.
• Experience working with or optimizing components related to knowledge graphs, neuro/symbolic reasoning, or GenAI systems.