---
title: 'Solution Engineer at RelationalAI'
canonical: 'https://feeny.ai/job/solution-engineer-relationalai-remote-46dpwbqnrrvt'
type: 'job'
last_seen: '2026-09-10'
---

# Solution Engineer at RelationalAI

- **Company:** RelationalAI
- **Location:** Remote
- **Work type:** remote
- **Posted:** 2026-09-03
- **Last confirmed live:** 2026-09-10
- **Apply:** https://job-boards.greenhouse.io/relationalai/jobs/6175260004

## Job description

## 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.

## The Role

You will be embedded inside our customers' hardest problems, and you will own the outcome until it works in production.

You'll sit with executives, domain experts, and data teams to find the decisions that actually move their business - inventory that's in the wrong place, risk concentrations nobody can see, fraud patterns that only emerge across three systems, capacity plans built on guesses. Then you'll model their world in our ontology, formulate the reasoning problem, write the PyRel, and ship something that runs against their real data in their own Snowflake account.

Every engagement here produces two deliverables.

The first is the one the customer sees: a working decision system that changes how they operate.

The second is the one that matters most to us: the pile of things you had to invent because our platform didn't have them yet. The modelling pattern you hand-rolled. The constraint formulation that should have been a primitive. The three-hour workaround where an API should have existed. You bring those back, you argue for them, and the strongest of them become product.

That second deliverable is why this role exists. If you only ever deliver the first one, we've hired a consultant. We're not hiring consultants.

You'll operate with unusual autonomy: you decide what's worth building, when a workaround is acceptable and when it's technical debt we'll regret, and when to tell a customer their real problem is not the one they asked about. You'll be technical enough that when something breaks in a customer environment, you find the root cause yourself rather than filing a ticket and waiting.

## What You'll Do

- Own outcomes end to end - discovery, modelling, implementation, performance tuning, production hardening, and the measurement that proves it worked. Not a handoff at each stage. Yours.
- Build, not describe - design and ship decision solutions on our modelling, reasoning, and learning stack: ontologies over customer data, rules, graph analytics, optimisation formulations, predictive models
- Fill the gaps yourself - when a customer workflow is blocked on something the platform doesn't do, scope it and build it. Then push the general version upstream: read our source, form a hypothesis before you escalate, open the PR.
- Close the loop with Product - every deployment generates a signal. Bring back reproductions, patterns, and specific failure modes ("the only way I could express this was by abusing X in this way"), not vibes. You are one of the loudest inputs into our roadmap.
- Run technical discovery that gets to the truth - workshops, demos, and proofs of concept designed to find out whether we can actually solve the problem, not to look impressive.
- Leave things better than you found them - document as you go, in the repo, same week. Turn one-off work into reusable reference implementations so the next person starts where you finished. No branch of yours should be diverging for a month.
- Refuse shortcuts that compound - no undocumented config drift, no "it works now" without knowing why it broke, no restarting the service before you've captured the evidence.

## Who You Are

You thrive in ambiguity and move with intent. You're motivated by deep understanding and meaningful impact.

- Owner, not participant. You take full accountability for the outcome, not your slice of it. When something is broken and it's nobody's job, it becomes yours.
- You build. Your instinct in the face of a hard problem is to open an editor, not a deck. You'd rather show a working prototype on real data than a diagram of one.
- High conviction, low ego. You argue hard for what you believe, you're direct about what's wrong, and you change your mind quickly when the evidence turns. You challenge ideas without making it personal - people leave arguments with you feeling sharper, not smaller.
- Rigorous. You root-cause things. You can explain both why it broke and why your fix works. Surface symptoms don't satisfy you.
- Fast in unfamiliar territory. Dropped into a codebase, a domain, or a data model you've never seen, you're useful within days. "I only do backend" and "that's not my job" are phrases you don't use.
- High tolerance for friction. Enterprise environments are messy - broken data, VDI access, security reviews, politics. You route around it and keep shipping.
- Impact-driven. You want the thing you built to still be running, and still be load-bearing, two years from now.

What This Role Is Not

We'd rather be blunt than waste your time:

- It is not demo-and-handoff pre-sales. You don't disappear after the POC; you're there when it goes to production.
- It is not staff augmentation. You own outcomes, not hours or ticket queues.
- It is not advisory. We deliver working software, not recommendations.
- It is not a support role. You deploy new things; you don't maintain someone else's legacy.

## Qualifications

- 5+ years building and shipping production software, at least some of it inside customer or partner environments
- Demonstrated end-to-end ownership: you have personally taken something from an ambiguous problem statement to running in production, and you can walk us through the whole arc, including what went wrong
- Strong SQL and deep familiarity with cloud data platforms (Snowflake, BigQuery, Databricks, Redshift)
- Strong programming ability - Python primarily; comfort with declarative or logic-style languages is a real advantage
- Comfortable reading unfamiliar source code, interpreting stack traces, and debugging systems you didn't write
- Able to hold your own with both a VP of Supply Chain and a staff data engineer, in the same meeting
- Comfortable operating in high-autonomy, high-velocity, low-instruction environments

## Preferred Qualifications

- Built analytical, decision, or reasoning applications that reached production and stayed there
- Experience with optimization, constraint solving, rule engines, graph algorithms, or ML on structured data
- Semantic modelling, data pipelines, and governance in real enterprise settings
- Track record of upstream contribution - features, tools, or abstractions you built for one customer that became standard for everyone
- Prior experience in enterprise technology, AI, or analytics platforms

## How We Hire

Our loop is designed to test the job, not trivia. Expect a technical screen; a session where you navigate and extend a system you've never seen before; a problem-decomposition session on a realistic customer scenario; and a conversation about ownership with the hiring manager. We're looking for how you think when you don't know the answer.

The Solution Engineer position offers a base salary range of $170,000 to $200,000, along with equity and comprehensive benefits. Please note that this range serves as a guideline; actual total compensation may vary based on factors such as experience, skill set, qualifications, and geographic location.

## Why RelationalAI

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 Apply

If 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.

Privacy Policy: EU residents applying for positions at RelationalAI can see our Privacy Policy [here](https://relational.ai/gdpr).

California residents applying for positions at RelationalAI can see our Privacy Policy [here](https://relational.ai/ccpa-notice)

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.

## About RelationalAI

## Company Overview
- **One-liner**: RelationalAI builds a decision intelligence platform native to Snowflake that combines semantic modeling with advanced reasoning to help enterprises move from AI experimentation to operational intelligence.
- **Entity Type**: Private (Series C)
- **Headquarters**: Berkeley, California, United States
- **Founded**: 2017
- **Founders**: Molham Aref (CEO), Marco Diciolla, and others

## Core Business
- **Industries**: Decision Intelligence, Artificial Intelligence, Data Cloud, Enterprise AI
- **Target Customers**: B2B, Enterprise organizations with complex data environments and decision-making needs, particularly those using Snowflake
- **Mission/Purpose**: To teach AI to reason like your business does, bridging the gap between AI-generated insights and actual operational decisions by building a system that understands business context and logic.

## Products & Services
- **Rel (Decision Agent)**: An AI decision agent aligned to a business’s semantic model, grounded in relational knowledge graphs, and powered by advanced reasoners. It can analyze all tables and documents inside Snowflake, build a business model, enrich it with business intuition, and reason over it to answer complex questions and drive decisions.
- **RelationalAI Decision Intelligence Platform**: The underlying platform that includes graph reasoners, rule-based reasoners, predictive and prescriptive analytics, all running natively inside Snowflake. It supports zero-copy cloning, versioning, time-travel, and consumption-based pricing.
- **Superalignment Methodology**: A proprietary approach that fine-tunes LLMs securely inside the data cloud, enriching them with semantic models and relational knowledge graphs to ensure AI stays grounded in business reality. When a user corrects the system, the update is permanent—no retraining or drift.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Total Funding**: $97.5M (as of Series C)
- **Latest Funding Round**: Series C ($22.5M raised approximately 6 months ago, per CB Insights)
- **Key Metric**: 170+ professionals across 26 countries, including 100+ engineers and 50+ PhDs
- **Notable Investors/Partners**: Tiger Global Management, Addition, Madrona Venture Group, Menlo Ventures, Snowflake Ventures, AT&T Ventures, and industry leaders like Bob Muglia and Satya Nadella
- **Growth Signals**: Recognized in the 2026 Magic Quadrant for Data and Analytics (Gartner), achieved #1 accuracy on the Spider 2.0 benchmark for SQL reasoning using superalignment, has earned over 35 research awards, and collaborates with researchers at more than 20 universities while publishing at top conferences.

## Competitive Advantages
- **Snowflake-Native Architecture**: Operates directly inside Snowflake, eliminating data movement, syncs, and impedance mismatch, which reduces complexity and fragility.
- **Knowledge Compounding**: When the system learns a business rule or is corrected, that knowledge persists and compounds across the organization—no retraining required, no drift.
- **Multi-Modal Reasoning**: Combines graph reasoning, rule-based reasoning, predictive and prescriptive analytics in a single platform, offering much deeper decision support than LLMs alone.
- **Heavy R&D Backing**: 50+ PhDs on staff, publishing at top conferences, collaborating with 20+ universities, and achieving top benchmark results.

## Strategic Focus
- **Decision-Grade AI**: Moving beyond standard AI “insights” (summarization, retrieval, generation) to actual operational decision-making that delivers measurable ROI.
- **Deep Enterprise Embedding**: Scaling the platform as a critical layer within the Snowflake ecosystem, making it the standard for enterprise business logic and decision automation.
- **Agent Alignment**: Continuously improving superalignment methodology to ensure AI agents remain grounded in dynamic business realities.
- **Product Development**: Expanding the “Rel” decision agent and the underlying reasoner capabilities to cover more use cases and verticals.

## Why Work Here
- **Remote-First Culture**: The company is remote-first and headquartered in Berkeley, CA, with 170+ teammates across 26 countries, offering a high degree of flexibility.
- **Deep Technical Challenges**: Work involves cutting-edge AI, semantic modeling, graph databases, reasoning engines, and optimization—a compelling environment for top-tier engineers and researchers.
- **Strong Research Orientation**: With 50+ PhDs, collaboration with 20+ universities, and 35+ research awards, there is a tangible emphasis on pushing the state of the art.
- **Core Values**: Customer centricity, transparency (radical candor), collaboration, innovation, and execution—values that suggest a balanced, high-accountability culture.
- **Mature Stage with Startup Energy**: Series C funded with $97.5M total raised, backed by top-tier investors, but still relatively small (170 people) allowing for outsized individual impact.
- **Career Growth**: (General job postings available via Greenhouse, though currently limited listings.)

## Sources
1. [relational.ai - Company](https://relational.ai/company)
2. [relational.ai - Product](https://www.relational.ai/)
3. [CB Insights - RelationalAI](https://www.cbinsights.com/company/relationalai)
4. [LinkedIn - RelationalAI](https://www.linkedin.com/company/relationalai)
5. [Greenhouse - RelationalAI Careers](http://job-boards.greenhouse.io/relationalai)

## Other roles at RelationalAI

- [Customer Support Engineer](https://feeny.ai/job/customer-support-engineer-relationalai-united-states-2sr56bqwn4p7) — United States
- [Don’t see what you’re looking for?](https://feeny.ai/job/don-t-see-what-you-re-looking-for-relationalai-remote-n99vtvstqq6k)
- [Solution Engineer](https://feeny.ai/job/solution-engineer-snowflake-colombia-3cf4hpmqq9ye) — Colombia
- [Solution Engineer](https://feeny.ai/job/solution-engineer-apiiro-united-states-pz8wkmdfw75k) — United States
- [Solution Engineer](https://feeny.ai/job/solution-engineer-asg-detroit-5mhde9bcy2sx) — Detroit, MI
- [Solution Engineer](https://feeny.ai/job/solution-engineer-field-nation-minnesota-d97f0kpmrdsx) — Minnesota
- [Solution Engineer](https://feeny.ai/job/solution-engineer-ghx-location-tf3md4z82yd6) — Location, OR / United States
- [Solution Engineer](https://feeny.ai/job/solution-engineer-snowflake-atlanta-5tsr8hezqvjr) — Atlanta, GA
- [Solution Engineer](https://feeny.ai/job/solution-engineer-avepoint-madrid-q4mc6b75cs8c) — Madrid, Spain
- [Solution Engineer](https://feeny.ai/job/solution-engineer-snowflake-new-york-crvrkfqmp4zp) — New York, NY