{"schemaVersion":"jobsearcher.job.v1","id":"96345a3fb6a7204d13f6a9ce","url":"https://jobsearcher.com/jobs/96345a3fb6a7204d13f6a9ce","canonicalUrl":"https://jobsearcher.com/jobs/96345a3fb6a7204d13f6a9ce","title":"Solution Engineer","description":"Who We Are\n\nAt 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.\n\nFrontier models are trained almost entirely on public data — they can speak about the world, but they don’t understand your business. We fix that.\n\nRelationalAI has pioneered a breakthrough called Superalignment — technology that enables LLMs to learn natively from private, structured enterprise data inside the data cloud.\n\nBy 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.\n\nWe’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.\n\nIf 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 .\n\nThe Role\n\nYou will be embedded inside our customers' hardest problems, and you will own the outcome until it works in production.\n\nYou'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.\n\nEvery engagement produces two deliverables.\n\nThe first is the one the customer sees: a working decision system that changes how they operate.\n\nThe 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 w an API should have existed. You bring those back, you argue for them, and the strongest of them become product.\n\nThat 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.\n\nYou'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.\n\nWhat You'll Do\nOwn 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.\nBuild, 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\nFill 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.\nClose 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.\nRun 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.\nLeave 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 w you finished. No branch of yours should be diverging for a month.\nRefuse 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.\nWho You Are\n\nYou thrive in ambiguity and move with intent. You're motivated by deep understanding and meaningful impact.\n\nOwner, 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.\nYou 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.\nHigh 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.\nRigorous. You root-cause things. You can explain both why it broke and why your fix works. Surface symptoms don't satisfy you.\nFast 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.\nHigh tolerance for friction. Enterprise environments are messy - broken data, VDI access, security reviews, politics. You route around it and keep shipping.\nImpact-driven. You want the thing you built to still be running, and still be load-bearing, two years from now.\nWhat This Role Is Not\n\nWe'd rather be blunt than waste your time:\n\nIt is not demo-and-handoff pre-sales. You don't disappear after the POC; you're t when it goes to production.\nIt is not staff augmentation. You own outcomes, not hours or ticket queues.\nIt is not advisory. We deliver working software, not recommendations.\nIt is not a support role. You deploy new things; you don't maintain someone else's legacy.\nQualifications\n5+ years building and shipping production software, at least some of it inside customer or partner environments\nDemonstrated 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\nStrong SQL and deep familiarity with cloud data platforms (Snowflake, BigQuery, Databricks, Redshift)\nStrong programming ability - Python primarily; comfort with declarative or logic-style languages is a real advantage\nComfortable reading unfamiliar source code, interpreting stack traces, and debugging systems you didn't write\nAble to hold your own with both a VP of Supply Chain and a staff data engineer, in the same meeting\nComfortable operating in high-autonomy, high-velocity, low-instruction environments\nPreferred Qualifications\nBuilt analytical, decision, or reasoning applications that reached production and stayed t\nExperience with optimization, constraint solving, rule engines, graph algorithms, or ML on structured data\nSemantic modelling, data pipelines, and governance in real enterprise settings\nTrack record of upstream contribution - features, tools, or abstractions you built for one customer that became standard for everyone\nPrior experience in enterprise technology, AI, or analytics platforms\nHow We Hire\n\nOur loop is designed to test the job, not trivia. Expect a technical screen; a session w 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.\n\nThe 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.\n\nWhy RelationalAI\n\nAt RelationalAI, you will:\n\nWork from anyw in the world\nEarn competitive salary + equity\nEnjoy open PTO, flexible schedules, and recharge weeks\nAccess global benefits, mental-health support, and learning stipends\nJoin a transparent, inclusive, and globally connected culture that values curiosity, excellence, and impact\nRegular team offsites and global events – Building strong connections while working remotely through team offsites and global events that bring everyone together.\nA culture of transparency & knowledge-sharing – Open communication through team standups, fireside chats, and open meetings.\n\nCountry Hiring Guidelines:\n\nRelationalAI hires people from around the world. All of our roles are remote; however, some locations might carry specific eligibility requirements.\n\nBecause of this, understanding location & visa support helps us better prepare to onboard our colleagues.\n\nOur People Operations team can help answer any questions about location after starting the recruitment process.\n\nHow to Apply\n\nIf 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.\n\nJoin us and help build the reasoning layer for the modern enterprise.\n\nPrivacy Policy: EU residents applying for positions at RelationalAI can see our Privacy Policy .\n\nCalifornia residents applying for positions at RelationalAI can see our Privacy Policy\n\nRelationalAI 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.","company":"Relationalai","rawCompany":"relationalai","city":"Myrtle Point","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-09-28T11:44:18.493Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1211.00","title":"Computer Systems Analysts","slug":"computer-systems-analysts"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Solution Engineer","description":"Who We Are\n\nAt 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.\n\nFrontier models are trained almost entirely on public data — they can speak about the world, but they don’t understand your business. We fix that.\n\nRelationalAI has pioneered a breakthrough called Superalignment — technology that enables LLMs to learn natively from private, structured enterprise data inside the data cloud.\n\nBy 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.\n\nWe’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.\n\nIf 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 .\n\nThe Role\n\nYou will be embedded inside our customers' hardest problems, and you will own the outcome until it works in production.\n\nYou'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.\n\nEvery engagement produces two deliverables.\n\nThe first is the one the customer sees: a working decision system that changes how they operate.\n\nThe 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 w an API should have existed. You bring those back, you argue for them, and the strongest of them become product.\n\nThat 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.\n\nYou'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.\n\nWhat You'll Do\nOwn 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.\nBuild, 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\nFill 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.\nClose 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.\nRun 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.\nLeave 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 w you finished. No branch of yours should be diverging for a month.\nRefuse 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.\nWho You Are\n\nYou thrive in ambiguity and move with intent. You're motivated by deep understanding and meaningful impact.\n\nOwner, 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.\nYou 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.\nHigh 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.\nRigorous. You root-cause things. You can explain both why it broke and why your fix works. Surface symptoms don't satisfy you.\nFast 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.\nHigh tolerance for friction. Enterprise environments are messy - broken data, VDI access, security reviews, politics. You route around it and keep shipping.\nImpact-driven. You want the thing you built to still be running, and still be load-bearing, two years from now.\nWhat This Role Is Not\n\nWe'd rather be blunt than waste your time:\n\nIt is not demo-and-handoff pre-sales. You don't disappear after the POC; you're t when it goes to production.\nIt is not staff augmentation. You own outcomes, not hours or ticket queues.\nIt is not advisory. We deliver working software, not recommendations.\nIt is not a support role. You deploy new things; you don't maintain someone else's legacy.\nQualifications\n5+ years building and shipping production software, at least some of it inside customer or partner environments\nDemonstrated 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\nStrong SQL and deep familiarity with cloud data platforms (Snowflake, BigQuery, Databricks, Redshift)\nStrong programming ability - Python primarily; comfort with declarative or logic-style languages is a real advantage\nComfortable reading unfamiliar source code, interpreting stack traces, and debugging systems you didn't write\nAble to hold your own with both a VP of Supply Chain and a staff data engineer, in the same meeting\nComfortable operating in high-autonomy, high-velocity, low-instruction environments\nPreferred Qualifications\nBuilt analytical, decision, or reasoning applications that reached production and stayed t\nExperience with optimization, constraint solving, rule engines, graph algorithms, or ML on structured data\nSemantic modelling, data pipelines, and governance in real enterprise settings\nTrack record of upstream contribution - features, tools, or abstractions you built for one customer that became standard for everyone\nPrior experience in enterprise technology, AI, or analytics platforms\nHow We Hire\n\nOur loop is designed to test the job, not trivia. Expect a technical screen; a session w 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.\n\nThe 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.\n\nWhy RelationalAI\n\nAt RelationalAI, you will:\n\nWork from anyw in the world\nEarn competitive salary + equity\nEnjoy open PTO, flexible schedules, and recharge weeks\nAccess global benefits, mental-health support, and learning stipends\nJoin a transparent, inclusive, and globally connected culture that values curiosity, excellence, and impact\nRegular team offsites and global events – Building strong connections while working remotely through team offsites and global events that bring everyone together.\nA culture of transparency & knowledge-sharing – Open communication through team standups, fireside chats, and open meetings.\n\nCountry Hiring Guidelines:\n\nRelationalAI hires people from around the world. All of our roles are remote; however, some locations might carry specific eligibility requirements.\n\nBecause of this, understanding location & visa support helps us better prepare to onboard our colleagues.\n\nOur People Operations team can help answer any questions about location after starting the recruitment process.\n\nHow to Apply\n\nIf 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.\n\nJoin us and help build the reasoning layer for the modern enterprise.\n\nPrivacy Policy: EU residents applying for positions at RelationalAI can see our Privacy Policy .\n\nCalifornia residents applying for positions at RelationalAI can see our Privacy Policy\n\nRelationalAI 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.","datePosted":"2026-09-28T11:44:18.493Z","dateModified":"2026-09-28T11:44:18.493Z","hiringOrganization":{"@type":"Organization","name":"Relationalai","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Myrtle Point","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"96345a3fb6a7204d13f6a9ce"},"url":"https://jobsearcher.com/jobs/96345a3fb6a7204d13f6a9ce"}}