As a contract Senior Knowledge Engineer, Ontology and Data Standards, you will drive how our team represents biological knowledge At Altos
We have built the machinery: a large canonical LinkML/Biolink schema including REST/MCP/CLI service layer; specification packages covering multiple prior-knowledge sources; and an agentic / human-in-the-loop curation framework. What it lacks is a technical owner-someone to govern and administer the content.
You are the scientific translation layer between biological discovery and AI platform engineering. You will elicit implicit models from bench and computational scientists, encode them rigorously, and utilize the agentic workflows that scale curation beyond what manual review can reach.
This role carries explicit decision rights: review authority on canonical schema change, ownership of the curation conventions that data atlas and engineering teams follow.
Key Responsibilities
Knowledge Modeling & Ontology Engineering:
Design, maintain, and extend internal LinkML / Biolink models and ontologies covering experimental and prior-knowledge metadata-driven by competency questions from user requirements and not by source-side convenience.
Own mapping and alignment as a discipline: cross-ontology mappings with recorded justification and provenance, and upstream term requests as appropriate.
Serve as reviewer of record for schema change, holding the line that reuse precedes coining anything new.
Agentic & Automated Curation:
Administer, steer, and refine our agentic curation framework and Model Context Protocol (MCP) service layer to scale data profiling, validation, and entity mapping far beyond manual capacity.
Standardize tool definitions (FastMCP), prompt templates, and LLM-driven workflows that extract, normalize, and validate metadata from prior-knowledge sources and experimental assets.
Biological Data Harmonization:
Define mapping patterns and metadata conventions for diverse experimental modalities (genomics, single-cell, screening data) to conform to the canonical schema.
Establish standardized conventions that allow both external prior-knowledge sources and internal experimental datasets to cleanly map into the LinkML graph architecture.
Quality, Evaluation & Provenance:
Establish and maintain automated validation, LLM-assisted quality control, and CI/CD under a "curation as code" paradigm-extending existing drift and coverage gates into the places where semantic review is still manual.
Measure whether the knowledge is correct, not merely reproducible: gold-standard sets, inter-curator agreement, and precision/recall on automated extraction.
Who You Are
Education & Experience: PhD with 5+ years, or MS with 8+ years, in Bioinformatics, Computational Biology, Genomics, Systems Biology, or a related life science field. This is a senior individual-contributor role with organization-wide technical authority and no direct reports.
Biological Data Lifecycle: Direct experience turning messy, real-world exploratory datasets (genomics, single-cell, screening, imaging) into structured metadata.
Ontology & Semantic Web Expertise: Strong working knowledge of OBO Foundry standards, OWL, RDF, and SPARQL, with schema modeling experience in LinkML, Biolink, or BioCypher. Experience with Protégé, ROBOT, ODK, or SSSOM mapping sets is a plus.
Python & Agentic AI Tooling: Proficient in modular Python (3.12, uv, pandas, Pydantic, pytest), and able to read and extend a substantial existing codebase rather than only scripting against it. Active hands-on experience with AI environments (e.g., Cursor, Claude Code) and building agentic LLM workflows, custom MCP tools, or RAG pipelines.
Software & Data Management: Familiarity with Git, GitHub Actions, graph/relational databases, and cloud storage (e.g., AWS S3).
The salary range for Redwood City, CA:
Senior Engineer: $105/hr to $123/hr
Exact compensation may vary based on skills, experience, and location.
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