Who We Are
At RelationalAI, we’re solving one of the most important challenges in artificial intelligence: how to teach large language models the logic, semantics, and business context of the modern enterprise.
Frontier models are trained almost entirely on public data — they can speak about the world, but they don’t understand your business. We fix that.
RelationalAI has pioneered a breakthrough called Superalignment — technology that enables LLMs to learn natively from private, structured enterprise data inside the data cloud.
By combining this with relational knowledge graphs and our proprietary neuro/symbolic-relational reasoners, we deliver trustworthy decision intelligence: systems that use semantic models to truly understand how a business operates and can reason across its data to drive better outcomes.
We’re a globally distributed team of engineers, scientists, and builders redefining how AI learns from data. We believe that high-stakes decisions deserve frontier intelligence — intelligence that’s explainable, aligned, and grounded in reality.
If you’re driven by curiosity, thrive in complexity, and want to help build the system that brings true understanding to enterprise AI, you’ll feel right at home here.
A proactive problem-solver who takes full ownership of customer and team challenges. You embrace opportunities to explore unfamiliar system components with enthusiasm and curiosity. Your approach combines technical excellence with data-driven analysis to deliver optimal solutions. While maintaining high standards, you demonstrate genuine empathy toward both colleagues and customers, creating a collaborative environment where relationships and results flourish together.
In this role, you'll tackle this through building advanced profiling and observability infrastructure, working with teams to fix performance issues (or just fixing them yourselves), and contributing to design reviews across the organization to ensure a performance-oriented mindset and culture through Engineering. We’re solving difficult problems at RelationalAI, and in Performance Engineering, you get to touch it all: distributed systems, database internals, mathematical optimization solvers, GNNs, GraphRAG, and other GenAI.
You’ll have :
- 7+ years of experience in performance engineering and benchmarking, focusing on large-scale data systems.
- Experience with distributed tracing and observability tools like Datadog, Honeycomb, LogicMonitor, or something similar.
- We’re language agnostic (but if you’re curious, we mostly use Python and Go)
- Extensive hands-on experience with performance engineering methodologies and best practices.
- Expertise in identifying and resolving performance bottlenecks using profiling tools and tracing.
- Deep understanding of distributed computing systems and architecture, with a focus on data-intensive applications.
- A proven track record of collaborating with other engineering teams to drive customer-centric outcomes.
Compensation Range of $140,000 to $220,000, depending on experience level and location.
At RelationalAI, you will:
- Work from anywhere in the world
- Earn competitive salary + equity
- Enjoy open PTO, flexible schedules, and recharge weeks
- Access global benefits, mental-health support, and learning stipends
- Join a transparent, inclusive, and globally connected culture that values curiosity, excellence, and impact
- Regular team offsites and global events – Building strong connections while working remotely through team offsites and global events that bring everyone together.
- A culture of transparency & knowledge-sharing – Open communication through team standups, fireside chats, and open meetings.
Country Hiring Guidelines:
RelationalAI hires people from around the world. All of our roles are remote; however, some locations might carry specific eligibility requirements.
Because of this, understanding location & visa support helps us better prepare to onboard our colleagues.
Our People Operations team can help answer any questions about location after starting the recruitment process.
How to ApplyIf you’re driven by understanding, powered by curiosity, and ready to help shape the next era of enterprise intelligence — we’d love to hear from you.
Join us and help build the reasoning layer for the modern enterprise.
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California residents applying for positions at RelationalAI can see our Privacy Policy here
RelationalAI is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
Top Skills
What We Do
Knowledge Graphs without Compromises
At RelationalAI, we are building the world’s fastest, most scalable, most expressive, most open relational knowledge graph management system (RKGMS), built on top of the world’s only complete relational reasoning engine that uses the knowledge and data captured in enterprise databases to learn and reason.
The results are stunning.
World-class talent driving knowledge graph innovation
We believe that future enterprise systems will be built with relational knowledge graphs as a foundation and that each component of the system will either be learned (via machine learning) or declared (via a reasoner).
The days of instructing the computer, step-by-step, on how to perform a task will be behind us.
Systems built this way, with fewer compute and human resources will increase margins, accelerate growth, and strengthen defensive moats.
At RelationalAI, we have brought together a group of leading researchers, data scientists, computer scientists and software engineers with extensive experience applying novel technologies to a wide range of complex problems in multiple industries.
Our team benefits from this unique combination of in-house expertise and active collaboration with the world’s foremost research institutions in areas ranging from machine learning and operations research to databases and programming languages. This collaboration regularly yields award-winning publications at the most respected academic conferences and journals.
