Clinical Research Engineer Jobs

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Protocol Data Engineer

A P Ventures LLC Remote 🌍 Remote

Remote

Today

Full time Amazon Web Services Artificial Intelligence AWS

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Job Description

A P Ventures LLC is supporting an FDA proof of concept for AI-assisted clinical trial protocol review. This remote role combines hands-on database engineering with structured protocol data modeling to help turn approved standards and technical models into scalable data structures, retrieval workflows, and traceable outputs within FDA-approved environments.

You will work alongside clinical protocol, data standards, architecture, interoperability, and AI/prompt engineering SMEs to operationalize structured protocol data models for both ICH M11-aligned and historical protocols, enabling reviewer-facing use supported by rigorous data quality practices.

Responsibilities

Implement protocol data structures and physical schemas for extraction, normalization, storage, retrieval, comparison, and reviewer-facing use of ICH M11-aligned and historical protocols.
Translate approved models including ICH M11, CDISC USDM, ontology, metadata, and terminology into practical database structures and data-engineering components for the proof of concept.
Develop and support ETL/ELT pipelines and data transformations for protocol content and structured outputs, preserving source provenance, metadata, assumptions, validation status, and reviewer feedback.
Collaborate with AI/prompt engineering and standards SMEs on RAG and semantic retrieval capabilities, including indexing, evidence caching, and protocol comparison components.
Support integration with FDA-furnished Elsa/HALO capabilities and FDA-approved data services, including PostgreSQL and/or HALO/Databricks, for evidence caching, retrieval, analytics, and dashboard-ready outputs.
Build advanced SQL and data-access logic for protocol extraction, historical retrieval and comparison, reviewer dashboards, and traceability to source evidence.
Perform data-focused quality assurance, reconciliation, validation, and regression testing, including checks for completeness, mapping consistency, retrieval quality, unsupported values, ambiguity, and reproducibility.
Document data models, interfaces, transformations, mappings, implementation decisions, technical limitations, and operational considerations to support FDA review, knowledge transfer, and future expansion.
Participate in FDA technical working sessions, proof of concept demonstrations, validation activities, and iterative refinement based on reviewer feedback.
Support implementation within FDA-provided platforms and approved data environments. Base effort is the proof of concept, without requiring a separate production platform.

Requirements

Extensive experience in database engineering, data architecture, information modeling, and analytics in complex enterprise environments.
Strong expertise in relational and dimensional data modeling, metadata management, ETL/ELT design, data warehousing, and data quality.
Advanced SQL skills, including PostgreSQL/PLpgSQL and/or Oracle PL/SQL; SQL Server experience is beneficial.
Experience with AWS data services and cloud database platforms such as Aurora PostgreSQL, Redshift, S3, Glue, Lambda, and DMS.
Experience integrating JSON/XML data and RESTful APIs; working knowledge of Python and CI/CD practices is beneficial.
Federal health, clinical research, or regulated-environment experience preferred; familiarity with FISMA/NIST controls is beneficial.
Must be able to obtain a High-Risk Public Trust.

Technologies

PostgreSQL, PLpgSQL, Oracle PL/SQL, SQL Server
AWS, Aurora PostgreSQL, Redshift, S3, Glue, Lambda, DMS
JSON, XML, RESTful APIs, Python, CI/CD
Elsa/HALO, HALO/Databricks, ETL/ELT
RAG, FISMA, NIST
ICH M11, CDISC USDM

Education

BS degree in Computer Science, Mathematics, Data Science, or a relevant technical field.

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