Senior AI Platform Engineer - Knowledge & Reasoning
Employer · Esko
Software developerSystems analystFull-timeBudapest
The Esko AI team is focused on leveraging AI to solve challenging customer problems. We are building knowledge and reasoning as a shared capability of Esko's AI Platform, enabling product teams to create AI-powered workflows grounded in trusted, contextual knowledge. As part of the platform team, you will help shape and build this capability, taking end-to-end ownership of substantial technical areas.
Tasks
- Design the knowledge representation: how constraints, transformations, procedures, and guidelines are modelled.
- Build and operate platform services for ingesting, curating, retrieving, and versioning knowledge.
- Define how semantic retrieval, deterministic validation, and human review work together.
- Design and implement reusable APIs and tools that allow AI systems and deterministic services to apply, validate, and explain contextual knowledge.
- Build evaluation suites covering retrieval quality, applicability, conflict and ambiguity handling, and explanation quality.
- Take end-to-end ownership of substantial technical areas, including their security, tenant isolation, reliability, observability, performance, and compatibility for consuming teams.
- Work directly with domain experts and product engineering teams to turn informal expertise into structured, testable knowledge.
Requirements
- Strong software engineering experience designing, building, and operating production systems in Python, TypeScript, Java, or a similar language.
- At least 5 years' experience in a software engineering role, preferably including ownership of a platform, API or other shared-services product used across multiple internal teams.
- Experience building knowledge, retrieval, or rule systems that other teams depend on, and the judgement to choose the right formalism for a problem.
- Practical experience with RAG, information extraction, and structured validation (JSON Schema, Pydantic, or equivalent).
- Sound judgement when reasoning about applicability, exceptions, missing evidence, and ambiguity.
- Experience constructing evaluation datasets, and the ability to write clearly about modelling decisions, tradeoffs, and failure modes.
- Undergraduate, Master's degree or PhD in Computer Science / Machine Learning / Data Science / Artificial Intelligence, or related disciplines.
- Comfort operating at the boundary between a platform team and the domain engineering teams that consume it.
- Excellent written and verbal communication, with the ability to work fluently with both technical and business stakeholders alike.