Solution Engineer

RelationalAI · AnywhereRemotomid

En corto

▸Ingeniero de soluciones que construye sistemas de toma de decisiones con IA para empresas, usando modelos lógicos y datos estructurados.
▸Trabajas directamente con clientes en problemas reales, modelas sus procesos, implementas soluciones en producción y mejoras la plataforma con lo que descubres.
▸Lo más destacado: tu trabajo no termina en la entrega; inventas soluciones que se convierten en producto para todos.

Fluent in English (written and spoken)

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Experiencia práctica con modelado de datos y lógica empresarial
✓Capacidad para construir soluciones técnicas desde cero en entornos reales
✓Habilidades de análisis para identificar problemas reales detrás de preguntas de clientes
✓Conocimiento de Python y su uso en problemas de razonamiento o optimización
✓Capacidad de trabajo autónomo y toma de decisiones técnicas
✓Comunicación clara con ejecutivos y equipos técnicos

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonPyRelRelational Knowledge GraphsNeuro/Symbolic-Relational ReasSnowflakeOntologiesGraph AnalyticsOptimization FormulationsPredictive ModelsSource Code (GitHub/PRs)

¿A quién escribirle en RelationalAI?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

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.

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