Customer Support Engineer
About the job
- At least 5 years of experience in a customer-facing support role.
- A Bachelor of Science or Master of Science degree in Computer Science, Engineering, or another technical field is strongly considered.
- Ability to troubleshoot technical issues and communicate with customers about their needs, questions, and concerns.
- Ability to handle support requests ranging from urgent to minor, including occasional scheduled off-hours work and on-call shifts.
- Technical understanding of RelationalAI products and how customers build, deploy, and manage applications using the platform.
- Ability to use artificial intelligence agents to accelerate troubleshooting and proactively propose code optimizations.
- Ability to triage issues using error messages, log files, thread dumps, stack traces, sample code, and other available data.
- Ability to troubleshoot performance issues involving customer technology and RelationalAI technology.
- Ability to advise on and troubleshoot client applications within customers' overall architectures.
- Ability to troubleshoot environment issues involving RelationalAI, Snowflake, and Azure.
- Background in database technologies and/or graph database technologies.
- Proficiency in programming languages such as Python and SQL.
- Learn RelationalAI products, support processes, and internal processes during the initial months.
- Work on customer support cases to develop the experience and insight needed to provide effective support.
- Become a subject matter expert in specific product areas for the Field Engineering team.
- Work with the Support Engineering team to improve and evolve the product and customer support.
- Collaborate with Sales, Field Engineering, and Product Engineering to understand and resolve customer issues completely and promptly.
- Streamline and improve processes, tools, RelationalAI product offerings, and the overall customer experience.
- Communicate with customer contacts including chief technology officers, management, developers, and operations teams.
- Provide guidance and insight through email, telephone, remote conferencing, and occasional in-person engagements.
- Work with Product Management and Product Engineering to define and drive fixes and enhancements addressing customer needs.
About the company
RelationalAI provides a fully managed cloud service that adds AI-powered semantic analysis to data clouds. Its core offering is an AI coprocessor that enhances semantic models and performs advanced data analysis, including graph analytics, to surface latent patterns in data. The service runs in the client’s cloud and stays in sync with the client’s data, enabling multiple AI techniques to be applied on a data-centric foundation. This allows teams to build intelligent applications with semantic layers for better decisions in real time. Compared with competitors, RelationalAI emphasizes a data-cloud–native approach that remains continuously aligned with the client’s data, providing richer semantic models and insights across use cases such as fraud detection, supply chain optimization, and contextual recommendations. The company’s goal is to help businesses derive actionable insights, improve efficiencies, and save costs by powering smarter, data-driven applications.
Company Size
51-200
Company Stage
Early VC
Total Funding
$97.5M
Headquarters
Berkeley, California
Founded
2017
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Simplify's Take
What believers are saying
- June 2026 launched Rel App, conversational CoWork, and push-button post-training.
- AT&T said RelationalAI powers billions of interactions and delivered 5x ROI last year.
- Gartner included RelationalAI in its inaugural 2026 Magic Quadrant for decision intelligence.
What critics are saying
- Snowflake controls distribution; RelationalAI's strategy depends on Snowflake's platform priorities.
- OpenAI, Claude, and GitHub Copilot already bundle agent skills, squeezing standalone differentiation.
- If Snowflake builds native reasoning, RelationalAI becomes a replaceable feature, not a company.
What makes RelationalAI unique
- RelationalAI runs decision intelligence natively inside Snowflake, avoiding data egress and governance breaks.
- Its Rel combines rule, graph, predictive, and prescriptive reasoners in one workflow.
- RelationalAI won Snowflake's 2026 Telecom Partner of the Year for enterprise decisioning.
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Benefits
Remote Work Options
Flexible Work Hours
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 5%2 year growth
↑ 3%Snowflake Ventures and AT&T Ventures have invested $22.5M in RelationalAI to accelerate the next stage of enterprise Decision Intelligence. The funding supports deeper integration with Snowflake Intelligence and expands delivery to joint customers like AT&T, advancing trusted, explainable AI that runs directly inside the Snowflake AI Data Cloud.
Researchers recognized with the 2026 Alberto O. Mendelzon Test-of-Time Award. August 11, 2026 Dana Sandu Research that stands the test of time is rare. This year, Mahmoud Abo Khamis, Hung Q. Ngo, and Atri Rudra received the 2026 Alberto O. Mendelzon Test-of-Time Award at PODS 2026 in Bengaluru, India, recognizing work whose influence has only grown over the past decade. Presented annually, the Alberto O. Mendelzon Test-of-Time Award honors a paper published in the ACM Symposium on Principles of Database Systems (PODS) proceedings ten years earlier that has had the greatest impact over the intervening decade - through research, methodology, or transfer into practice. The 2026 selection committee - Wang-Chiew Tan of Google (chair), George Fletcher of Eindhoven University of Technology, and Frank Neven of Hasselt University - selected a single paper for this year's award. Abo Khamis, Ngo, and Rudra were recognized for FAQ: Questions Asked Frequently (PODS 2016), which introduced the Functional Aggregate Query (FAQ) framework. Rather than treating relational query processing, constraint satisfaction, probabilistic graphical models, and algebraic computation as separate disciplines, the paper revealed a common mathematical structure underlying them all. That unifying perspective gave researchers across multiple communities a shared language - and a foundation for exchanging ideas that had previously evolved in isolation. The paper also introduced InsideOut, an algorithmic framework for efficiently evaluating Functional Aggregate Queries. Together, FAQ and InsideOut have shaped a decade of research in query optimization and computational reasoning. At RelationalAI, the FAQ framework forms the foundation of a key component of the company's query optimizer. In its citation, the committee describes the paper as "a quintessential example" of research whose importance has increased over time. Rather than solving only a timely technical challenge, the committee notes, FAQ established a way of thinking that continues to guide the field. Its lasting influence is reflected in extensive follow-on research, continued citations, and its enduring relevance to modern database systems - an impact first recognized with the PODS 2016 Best Paper Award. Hung Q. Ngo is VP of Research at RelationalAI, where he works on the company's query optimizer. Mahmoud Abo Khamis is a professor at the University of Oxford and a former researcher at RelationalAI. Atri Rudra is a professor of computer science at the University at Buffalo, SUNY. Congratulations to Mahmoud, Hung, and Atri on this well-deserved recognition.
RelationalAI recognized as One to Watch in Snowflake's Modern Marketing Data Stack report. June 22, 2026 AI/ML development and deployment solution drives marketing ROI for joint customers San Francisco, June 22, 2026 - RelationalAI, a leader in enterprise AI, today announced at Cannes Lions 2026 that it has been recognized by Snowflake, the AI Data Cloud company, as One to Watch in AI/ML development and deployment category in The Modern Marketing Data Stack: Governing the Agentic Enterprise. RelationalAI's powerful platform enables marketing teams to build and deploy AI-driven applications directly within Snowflake, turning siloed customer and campaign data into actionable insights without moving it elsewhere. Now in its fifth year, Snowflake's Modern Marketing Data Stack report reflects a major shift in how marketing organizations operate - from fragmented tools toward AI-driven, agentic systems built on governed data foundations. This edition draws on insights from more than 11,500 Snowflake customers and ecosystem partners across 13 categories, highlighting how organizations are enabling AI to move beyond assistance to decisioning and action across the marketing lifecycle, while addressing the growing demands of data gravity, privacy and trust. Marketing leaders are increasingly expected to do more with less, said Molham Aref, CEO of RelationalAI. Decision intelligence with RelationalAI empowers marketers to go beyond traditional analytics to build truly intelligent applications that drive engagement, conversations, and loyalty using the data they already have in Snowflake. This leads to personalized campaigns, predictive customer journeys, and timely churn detection. The result: measurable ROI. Legacy analytics tools that no longer deliver in the modern workplace, leaving marketing leaders unable to executive at the pace needed. RelationalAI solves that problem. As a Snowflake Native App, marketing teams are able to scale experimentation, iterate rapidly, and co-develop use cases across operations and analytics with no data migrations or costly integrations needed. RelationalAI gives organizations the ability to turn their data into action. With Snowflake Data Cloud as the foundation, marketing teams are now able to operationalize their most impactful marketing initiatives, said Denise Persson, Chief Marketing Officer at Snowflake. RelationalAI, Inc. is excited to see how RelationalAI continues advancing intelligent decision-making in the marketing space. About RelationalAI RelationalAI brings enterprise decision intelligence natively into the AI Data Cloud. Powered by rich semantic models, advanced reasoners, and context-enhanced LLMs, RelationalAI provides agents that understand your business and drive measurable ROI - all without moving data from where it already is. Its goal: AI that can help run a company, not just chat about it. Learn more at relational.ai.
RelationalAI closes the AI value gap with new agentic decision intelligence capabilities for the Snowflake AI Data Cloud. RelationalAI announced at Snowflake's annual user conference, Snowflake Summit 26, a series of new capabilities for Rel, its agentic decision intelligence system that runs natively in the Snowflake AI Data Cloud. With these new capabilities, joint customers can give decision agents the context, reasoning, and post-training needed to take action across the operations that drive the bottom line, including pricing, supply chain, network operations, and resource allocation. Generative AI has unlocked extraordinary value for software development, but most enterprises still see a gap between what AI can do and what they are getting from it across the rest of the business. Today's release introduces the new Rel App, alongside the prescriptive and predictive reasoners, conversational decision intelligence inside Snowflake CoWork, and RelationalAI "push-button" post-training. Together, they give decision agents what they need to act with confidence: a model of the enterprise for context, reasoners as tools, and post-training to turn a general-purpose model into a business expert. "Just like humans, agents have difficulty knowing how to make good decisions," said Molham Aref, Founder and CEO of RelationalAI. "With these capabilities running natively in the Snowflake AI Data Cloud, customers can close the AI value gap by giving their agents the context, tools, and post-training they need to take the best possible action in the face of uncertainty, at machine speed and at economics that scale across the enterprise." The new Rel App captures a shared, governed representation of how a business works: the concepts, relationships, and rules that define how decisions get made. Domain experts can explore the model, follow connections, ask questions in natural language, and reason through decisions, with every interaction grounded in their own data inside Snowflake. Today's release also includes RelationalAI's growing library of coding agent skills, which work across Snowflake CoCo, Claude Code, OpenAI Codex, and GitHub Copilot. Joint customers already use these skills to extend RelationalAI models directly from their preferred development environments, deepening the context their decision agents draw on. The general availability of the prescriptive reasoner gives Snowflake customers a purpose-built tool for solving constrained optimization problems. The predictive reasoner applies graph neural networks to enterprise data inside Snowflake to forecast outcomes like demand, churn, and asset failure. Paired with the prescriptive reasoner, the predictive reasoner gives decision agents a full path from forecast to recommended action in a single workflow, all without moving data off the platform. The RelationalAI suite of rule, graph, predictive, and prescriptive reasoners supports complex multi-domain reasoning in a single workflow. Decision agents working in Snowflake can now combine LLM-based reasoning with domain-specific reasoners, with measurable gains in accuracy and significant reductions in cost. As a launch partner in the Open Semantic Interchange (OSI) initiative, RelationalAI also enables enterprises with existing ontology deployments, such as Palantir, to port semantic models into Snowflake via OSI and run advanced reasoning on RelationalAI with no rebuild required. "At Snowflake, we're focused on enabling secure, high-performance AI directly where data lives," said Amy Kodl, SVP, Worldwide Alliances and Channels at Snowflake. "RelationalAI's Rel App extends these capabilities by introducing powerful reasoning and semantic modeling within the Snowflake AI Data Cloud, helping customers accelerate the development of intelligent agents and decision intelligence systems." RelationalAI also now powers conversational decision intelligence inside Snowflake CoWork letting business users ask ad-hoc questions in natural language and receive governed, semantically grounded answers from RelationalAI's reasoners directly on private data in the Snowflake AI Data Cloud. David Marshall has been involved in the technology industry for over 30 years, and he's been working with virtualization software since 1999. He became a pioneer in the virtualization and cloud computing field - one of the few people in the industry allowed to work with Alpha stage server virtualization software from industry leaders: VMware (ESX Server), Connectix and Microsoft (Virtual Server).Through the years, he has invented, marketed and helped launch a number of successful software companies and products. David holds a BS degree in Finance, an Information Technology Certification, and a number of vendor certifications. He's also co-authored two published books: "VMware ESX Essentials in the Virtual Data Center" and "Advanced Server Virtualization: VMware and Microsoft Platforms in the Virtual Data Center" and was the technical editor for two popular Virtualization "For Dummies" books. With his remaining spare time, David founded and operates one of the oldest independent modern data center publications, VMblog.com. And co-founded CloudCow.com, a publication dedicated to Cloud Computing. Since 2009, and each year thereafter, David has been honored with the vExpert distinction by VMware by Broadcom for his evangelism.Connect on LinkedIn: https://www.linkedin.com/in/davidmarshall/
RelationalAI named Snowflake 2026 Telecom Snowflake Product Partner of the Year. June 2, 2026 Company recognized for powering decision intelligence natively in the Snowflake AI Data Cloud, enabling telecom leaders to turn data into real-time, outcome-driven decisions San Francisco, June 2, 2026 - RelationalAI, a leader in enterprise AI, today announced at Snowflake's annual user conference, Snowflake Summit 2026, that it has been named the 2026 Telecom Snowflake Product Partner of the Year award winner by Snowflake, the AI Data Cloud company. For AT&T, AI has to understand the realities of its network, operations, customers, and other details of its business. RelationalAI, Inc. has focused on building practical, telco-grade AI that creates measurable value at scale, said Mark Austin, Vice President of Data Science at AT&T. RelationalAI has been an important collaborator in that journey, including GSMA Open Telco AI and multiple #1 submissions on key industry benchmarks. Their capabilities combined with Snowflake's governed data platform help move AI from simply answering questions to supporting better operational and commercial decisions across the business. Their recognition as Snowflake Telco Partner of the Year reflects the importance of moving beyond generic AI towards systems that can support real decisions in complex enterprise environments. RelationalAI was recognized for its achievements as part of the Snowflake AI Data Cloud, helping joint customers operationalize decision intelligence as a core control plane for AI-native infrastructure. Bringing enterprise decision intelligence natively to the Snowflake ecosystem, RelationalAI transforms Snowflake data into intelligent business decisions through advanced AI reasoning. This recognition from Snowflake highlights the growing importance of decision intelligence as a new layer in the enterprise stack, said Molham Aref, Founder and CEO of RelationalAI. Many enterprise organizations using AI stop at insights like summarizing, retrieving, or generating. RelationalAI bridges that gap with decision-grade reasoning inside Snowflake, and as organizations seek to unlock more value from their data, combining large-scale platforms with AI-driven reasoning will be critical to delivering smarter, more adaptive decision-making. As connectivity infrastructures evolve into strategic platforms, the ability to automate decisions is becoming essential to directly control outcomes, Amy Kodl, SVP, Worldwide Alliances & Channels at Snowflake. RelationalAI combines domain-specific intelligence with a universal decision layer that is built natively on the Snowflake AI Data Cloud. RelationalAI, Inc. is excited to recognize RelationalAI as the 2026 Telecom Snowflake Product Partner of the Year and continue to collaborate to bring even more advanced decisioning capabilities that are governed, auditable, and cross-domain to the AI Data Cloud. RelationalAI continues to set the standard for enterprise decision intelligence, with industry recognition across benchmarks, analyst reports, and standard bodies. Earlier this year, AT&T and RelationalAI contributed to #1 rankings on the Spider and TeleLogs benchmarks. RelationalAI was also named a launch partner for GSMA Open Telco AI, collaborating with AT&T to deliver 33 best-in-telco LLMs (OTel) as part of the launch. RelationalAI was also the only Snowflake-native vendor named the Gartner Magic Quadrant for Decision Intelligence. RelationalAI, together with Snowflake and other ecosystem partners, is helping lead the Open Semantic Interchange (OSI) Industry Initiative. About RelationalAI RelationalAI brings enterprise decision intelligence natively into the AI Data Cloud. Powered by rich semantic models, advanced reasoners, and context-enhanced LLMs, RelationalAI provides agents that understand your business and drive measurable ROI - all without moving data from where it already is. Its goal: AI that can help run a company, not just chat about it. Learn more at relational.ai.