Ontology Solution Architect

Role & responsibilities

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Role Overview

Solution Architect

Key Responsibilities

Architecture, Design & Governance

• Define end-to-end architecture across ingestion, extraction, transformation, semantic modeling, and visualization layers.
• Develop HLDs, LLDs, data flow diagrams, and system interaction models.
• Ensure all components follow enterprise architecture policies, security standards, responsible AI guidelines, and auditability requirements.
• Oversee architectural feasibility, scalability, and technical risk assessments.

Data Ingestion & Processing Architecture

• Architect processes for ingesting unstructured documents (PDF, text) and structured datasets.
• Design NLP-based extraction pipelines for entities, endpoints, outcomes, metadata, and summaries.
• Define and optimize processing workflows using cloud data engineering frameworks.

Visualization & API Architecture

• Design an extensible visualization framework for dashboards, evidence summaries, cross-study comparison, and drill-down analysis.
• Architect microservices and APIs for data retrieval, metadata access, and UI-server interactions.
• Ensure performance, scalability, and UX alignment across visualization components.

AI Governance, Traceability & Compliance

• Ensure AI/NLP pipelines follow responsible AI requirements including transparency, lineage, explainability, auditability, and reproducibility.
• Collaborate with compliance, privacy, and security teams to ensure data protection standards are met.

Cross-Functional Collaboration

• Work closely with product leads, domain SMEs, UX designers, data engineers, QA, and DevOps teams.
• Translate functional requirements into technical designs and sprint-ready engineering tasks.
• Support cross-stream alignment where ingestion, ontology, and analytics intersect.

Required Skills & Experience

Core Technical Expertise

• 10+ years of experience in architecture roles spanning cloud, data, analytics, and application integration.
• Strong expertise in:
• Cloud platforms (AWS preferred: Lambda, S3, API Gateway, IAM, EKS, Textract, Bedrock)
• Data engineering frameworks (Databricks, Delta Lake, ETL/ELT pipelines)
• NLP/AI extraction pipelines (document parsing, entity extraction, embeddings)
• Visualization platforms (Power BI, Tableau, Looker)
• Experience designing scalable, distributed data pipelines and microservice architectures.
• Knowledge of semantic/ontology modeling (RDF, OWL, SHACL) is highly desirable.

Domain & Functional Knowledge

• Background in scientific evidence, medical content, clinical data, or data-heavy regulated environments is beneficial.
• Experience with unstructured data processing, research document ingestion, or literature analysis is a plus.

Leadership & Delivery Skills

• Ability to drive technical decision-making and cross-team alignment.
• Strong communication skills, capable of presenting architecture to technical and non-technical audiences.
• Experience working in Agile environments with globally distributed teams.

Behavioral Competencies

• Structured, detail-oriented, and proactive problem solver.
• Strong analytical thinking and ability to simplify complex technical concepts.
• Effective collaborator across business, UX, engineering, and infrastructure teams.

Education & Certifications

• Bachelors or master's in computer science, Engineering, Information Systems, or related field.
• Cloud architecture certifications (AWS Architect preferred).
• Certifications in data engineering, analytics, or NLP are a plus.
• Agile/Scrum certifications (PSM/CSM) are beneficial.