Senior

Predictable Machines; Castilla y León; A distancia; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A cutting-edge AI company is seeking a Verification-Focused AI Engineer in Valladolid, Castilla y León. The ideal candidate will have a strong foundation in Computer Science or Mathematics and will be proficient in functional programming, particularly with Kotlin and TypeScript. This role requires building verification-first AI systems, developing formal verification tools, and a collaborative approach to software engineering. Flexibility and remote work are offered within a dynamic work environment.

Servicios

Flexible, remote-first working environment

Access to state-of-the-art AI tools and learning resources

Formación

• Experience with functional programming languages like Kotlin, TypeScript, or Scala.
• Understanding of event-driven architectures and streaming systems.
• Curiosity about formal methods, logical reasoning, and mathematical validation.

Responsabilidades

• Build verification-first AI systems.
• Develop and integrate formal verification tools.
• Design streaming verification workflows.
• Implement TypeScript client libraries for real-time verification.
• Contribute to Docker-based tool ecosystem for verification.
• Research new verification methodologies.

Conocimientos

Proficiency in functional programming languages

Strong foundation in Computer Science, Mathematics, or Engineering

Systems thinking mindset

Collaborative engineering skills

Educación

Degree in Computer Science, Mathematics, or Engineering

Herramientas

Kotlin

TypeScript

Descripción del empleo

Overview

Valladolid, Castile and Leon Predictable Machines

Predictable Machines is building the next generation of verifiable AI systems—combining cutting-edge language models with formal verification, functional programming, and mathematical rigor. We are seeking a Verification-Focused AI Engineer who thrives at the intersection of AI capabilities and mathematical precision.

Ideal candidates will understand both AI potential and limitations, embrace functional programming paradigms, have curiosity about formal methods, think in systems and workflows, and value transparency and explainability.

Responsibilities

• Build verification-first AI systems alongside senior engineers, focusing on Server-Sent Events architectures, streaming workflows, and real-time verification pipelines using Kotlin and TypeScript.
• Develop and integrate formal verification tools—work with SMT solvers, logical reasoning systems, and mathematical validation tools to ensure AI outputs are provably correct and traceable.
• Design streaming verification workflows that combine factual verification (web search), logical validation (formal methods), and mathematical checking (computational tools) into coherent, auditable pipelines.
• Implement TypeScript client libraries and UI components for real-time research steppers, verification progress visualization, and interactive audit trail interfaces with full type safety.
• Contribute to Docker-based tool ecosystem—help maintain and extend the 17+ containerized verification tools, MCP server implementations, and automated deployment systems.
• Participate in verification methodology research—explore new approaches to AI fact-checking, logical consistency testing, and mathematical validation while maintaining functional programming principles.
• Support enterprise integration patterns—help build authentication systems, multi-tenancy features, and API integrations that allow verification capabilities to be embedded in customer applications.

Qualifications

• Strong foundation in Computer Science, Mathematics, or Engineering—degree preferred but exceptional self-taught candidates with demonstrated systems-building experience welcome.
• Proficiency in functional programming languages—experience with Kotlin, TypeScript, or Scala preferred; comfort with immutable data structures, composable functions, and type-safe architectures.
• Interest in mathematical reasoning and formal methods—curiosity about logic, proof systems, SMT solvers, or mathematical validation (coursework or personal projects demonstrate this).
• Systems thinking mindset—experience with event-driven architectures, streaming systems, API design, or containerized applications; understanding that AI is part of larger, reliable systems.
• Collaborative engineering skills—comfort with Git workflows, code reviews, and building production-quality software rather than just research prototypes.

Bonus Points

• Formal methods exposure—coursework or projects involving theorem provers, model checking, constraint solving, or mathematical verification tools.
• LLM integration experience—but focused on reliability, evaluation, and systematic testing rather than just prompt engineering.
• Functional programming enthusiasm—personal projects or contributions to FP ecosystems; understanding of monads, type systems, or category theory.
• Enterprise software experience—authentication systems, multi-tenancy, observability, or building APIs that other developers actually use.
• Interest in AI safety/explainability—genuine curiosity about making AI systems transparent, auditable, and mathematically sound.
• Hands-on mentorship from experienced AI engineers and researchers.
• Opportunity to work on real projects with impact in the AI reliability space.
• Flexible, remote-first working environment.
• A chance to grow your skills and transition into a full-time role in a fast-growing company.
• Access to state-of-the-art AI tools and learning resources.

Requirements (Education and Experience)

• Strong foundation in Computer Science, Mathematics, or Engineering — degree preferred but exceptional self-taught candidates welcome.
• Proficiency in Kotlin, TypeScript, or Scala; immutable data structures and type-safe architectures.
• Interest in formal methods, logical reasoning, SMT solvers, or mathematical validation.
• Experience with event-driven architectures, streaming systems, and containerized deployments.
• Collaborative engineering experience with Git, code reviews, and production-quality software.

Note: This description consolidates responsibilities and qualifications from the provided material into a focused summary suitable for a single role. It preserves core information about the verification-focused AI engineering position and excludes extraneous duplication.