Lead Engineer - Agentic Systems

MindWalk is a global biologics discovery company integrating Bio-native AI, deep data, and advanced lab research to accelerate discovery and development of therapeutic, anti-drug and diagnostic antibodies, peptide-based therapies, vaccines and beyond. We deliver end-to-end solutions spanning target exploration, discovery, engineering, characterization, production, and humanization—available as full-service partnerships, existing asset co-development or modular SaaS access. We partner with leading biotech and pharmaceutical organizations, applying our unified biointelligence ecosystem to advance next-generation biologics that improve lives.

Job Description:

We're looking for a senior engineer who can move fluently between data architecture and formal ontology to build the foundation connecting biological data, scientific evidence, and agentic AI at MindWalk.

You'll set the information architecture (data domains, models, metadata, lineage) and the semantic layer (ontology, identity, evidence) as one coherent system, then make sure both hold up as they're consumed by LLM and agent workflows. This is a lead role: architecture and hands-on delivery in equal measure.

Key responsibilities:

• Model MindWalk's current- and target-state data and information architecture alongside its canonical semantic model, as a single connected system.
• Define identity, versioning, provenance, and evidence-modeling rules for biological entities, and the metadata/catalog structures that make them findable.
• Translate this into production: RDF/OWL, SHACL, schemas, APIs, and automated tests.
• Build typed, permission-aware interfaces so agent and LLM workflows can retrieve evidence and trace claims back to source.
• Set the versioning and CI/CD practices that keep the architecture and the ontology evolving safely together.
• Work directly with computational biologists, data and software engineers to keep the system grounded in real science and real production constraints.

Requirements:

• Senior, hands-on experience across both data architecture and formal ontology/knowledge representation, not just one.
• Practical expertise with RDF/RDFS, OWL 2, SHACL, SPARQL, and production data architecture (modeling, lineage, contracts).
• Experience with biomedical, pharmaceutical, or bioinformatics data, including its evidence and uncertainty.
• Experience delivering at least one LLM- or agent-based workflow with structured outputs, retrieval, and human review.
• An MSc or PhD in a relevant field, or equivalent experience, and comfort setting technical direction.
• Good written and oral communication skills in English.
• You are agile in planning and organizing your work. You are an excellent team player.

Strong candidates may also have:

• OBO Foundry standards, LinkML, ROBOT, or SSSOM.
• LangGraph, Model Context Protocol, or comparable agent frameworks.
• AWS, Terraform, and regulated or GxP-adjacent environments.