Technical Architect – AI & Knowledge Platforms

Osprey Life Sciences; Boston (MA); On-site; USD 180,000 - 240,000; Full time

Job summary

Osprey Life Sciences, LLC is seeking a hands-on Technical Architect to lead an AI-assisted knowledge platform initiative. You will own end-to-end architecture across ingestion, knowledge graph, and LLM grounding, evaluating platforms and driving prototyping, architecture validation, and code reviews.

You will define canonical data models for medical claims, ensure provenance, and guide decisions on tooling and standards.

Qualifications

• 10+ years of experience designing data, knowledge, integration, or information-platform architectures.
• Hands-on experience with AI/LLM-enabled solutions and knowledge graphs.
• Experience with RDF, SPARQL, and ontology modeling.

Responsibilities

• Define the end-to-end architecture for AI-assisted claim acquisition, extraction, knowledge modeling, graph storage, and LLM grounding and verification.
• Evaluate and recommend knowledge graph and semantic technology platforms (e.g., Semaphore, MANTIS, System Graph).
• Define the canonical data model for medical claims, supporting evidence, citations, and provenance.
• Assess LLM access strategies including AWS Bedrock and API access.
• Develop cost, performance, security, and token-management analyses to support platform decisions.
• Design the MCP server and LLM interface layer with authentication, authorization, auditing, and usage instrumentation.
• Establish standards for claim versioning, data lineage, provenance tracking, and semantic interoperability.
• Determine where FHIR, schema.org, or related semantic frameworks may be appropriate.
• Provide architectural guidance to the Technical Lead and engineering teams.
• Contribute to prototypes, code reviews, and technical validation.
• Prepare executive decision packages with platform recommendations.

Skills

Data architecture

AI/LLM architectures

Knowledge graphs

API design

Prototyping

Communication

Stakeholder collaboration

AWS Bedrock

Cost-performance analysis

Security & auth

Tools

RDF

SPARQL

Ontology modeling

MarkLogic

MANTIS

Semaphore

System Graph

Job description

Technical Architect – AI & Knowledge Platforms

A World Class Company

Osprey Life Sciences, LLC is a leading consulting and services firm specializing in providing comprehensive technology solutions for Life Sciences IT organizations. Our primary focus is on assisting these organizations in effectively and efficiently delivering solutions that support their business objectives and their mission to enhance human health and improve lives.

Position Overview

Osprey is seeking a hands-on Technical Architect to support an innovative proof-of-concept initiative for a medical publishing organization. The project will create a governed health information platform in which medically reviewed claims and supporting evidence are structured within a knowledge graph and made available to large language models to generate verified, cited responses.

The Technical Architect will own the end-to-end solution architecture across the AI-assisted ingestion pipeline, context normalization, knowledge graph and data-store layers, and the interface used to ground and verify LLM-generated answers.

This individual will evaluate technology options, establish architectural standards, and make practical build, buy, and defer recommendations. This is a hands-on position requiring direct involvement in prototyping, code reviews, and architecture validation—not a purely advisory role.

Key Responsibilities

• Define the end-to-end architecture for AI-assisted claim acquisition and extraction, knowledge modeling, graph storage, contextual normalization, and LLM grounding and verification.
• Evaluate and recommend knowledge graph and semantic technology platforms, including options such as Semaphore, MANTIS, and System Graph.
• Define the canonical data model for medical claims, supporting evidence, citations, and provenance.
• Assess LLM access strategies, including AWS Bedrock, direct API access, and smaller or open-weight models.
• Develop cost, performance, security, and token-management analyses to support platform decisions.
• Design the MCP server and LLM interface layer, including authentication, authorization, auditability, and usage instrumentation.
• Establish standards for claim versioning, data lineage, provenance tracking, and semantic interoperability.
• Determine where standards such as FHIR, schema.org, or related semantic frameworks may be appropriate.
• Provide architectural guidance to the Technical Lead and blended engineering team.
• Contribute directly to prototypes, proof-of-concept development, code reviews, and technical validation.
• Participate in weekly workstream checkpoints, biweekly demonstrations, and monthly architecture reviews.
• Help prepare the executive decision package, including recommendations regarding platform selection, production viability, staffing, costs, and next steps.

Required Qualifications

• 10+ years of experience designing data, knowledge, integration, or information-platform architectures.
• Demonstrated experience designing applied AI or LLM-enabled solutions.
• Hands-on experience with knowledge graphs and semantic technologies, including RDF, SPARQL, and ontology or taxonomy modeling.
• Experience architecting retrieval-augmented generation, LLM-grounding, or answer-verification solutions.
• Strong understanding of retrieval, citation, provenance, and validation approaches for generative AI.
• AWS architecture experience, including AWS Bedrock or a comparable managed LLM platform.
• Experience evaluating cost and performance tradeoffs among managed LLM services, direct APIs, and smaller or open-weight models.
• Experience designing secure APIs, MCP servers, or comparable interface layers for AI and agent-based applications.
• Ability to prototype solutions, review code, and validate architectural decisions directly.
• Strong communication and technical decision-making skills.
• Experience collaborating with engineering teams, business stakeholders, and external technology partners.

Preferred Qualifications

• Experience with MarkLogic as a document database or system of record.
• Healthcare, life sciences, medical publishing, or scientific-content experience.
• Familiarity with medical editorial, evidence-review, or governed-content workflows.
• Experience with FHIR, schema.org, or related healthcare and semantic standards.
• Hands-on experience with Claude, the Anthropic API, or Model Context Protocol.
• Experience guiding a proof of concept from technical evaluation through a production recommendation.
• Experience designing instrumentation that could support future usage, licensing, or billing models.

We offer an excellent compensation and benefits package with challenge and opportunity to learn, grow and contribute to a stimulating, fast-paced environment. Osprey is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status or any other characteristic protected by law.