Data & AI Engineer

• Location (Hybrid),Columbia, MD, 21046,United States

LOCATION: Hybrid – Columbia, MD

CLEARANCE: Must be able to obtain aHigh-Risk Public Trust

At APV,we’remore than a technology company —we’rea mission-driven powerhouse transforming organizations through advanced technology and human ingenuity. Ourexpertisespans AI/ML, data architecture, low-code/no-code development, Agile Dev Sec Ops , and cloud services, delivering scalable and meaningful solutions.

In our Emerging Technology Lab, innovation drives progress. Our teams create intelligent chatbots, AI-powered assistants, robotic process automation (RPA), essay graders, and data analytics platforms. Ifyou’repassionate about solving complex challenges and shaping the future, APV is the place for you. Since 2007,we’vepartnered with federal and state agencies to deliver IT, training, and consulting solutions that achieve mission-critical outcomes. Built on accountability, integrity, and quality, we go beyond expectations.

With 70+ prime contracts and a proven record of client success, APV continues to grow — andwe’relooking for exceptional talent to grow with us.

Provides hands-on data engineering and applied AI/LLM support for a federal proof of concept focused on AI-assisted clinical trial protocol review. The role works under senior technical and domain guidance to prepare protocol data, implement structured data components, configure and test LLM-based extraction workflows, and support traceable retrieval, comparison, and validation within federal approved environments.

• Implement and maintain protocol data structures and database components that support extraction, normalization, storage, retrieval, comparison, and reviewer-facing use of ICH M11-aligned and historical protocols.
• Develop and support ETL/ELT pipelines, Python-based data transformations, and data preparation workflows for protocol content and structured AI outputs while preserving source provenance, metadata, validation status, and reviewer feedback.
• Support development and testing of large language model (LLM) workflows for protocol information extraction, summarization, classification, normalization, and comparison, including prompt configuration and structured-output generation.
• Assist with retrieval-augmented generation (RAG), embeddings, semantic search, vector indexing, evidence retrieval, and context assembly used to ground LLM responses in protocol content and approved reference sources.
• Support integration of LLM and data workflows with FDA-furnished Elsa/HALO capabilities and approved data services, including PostgreSQL and/or HALO/Databricks, for evidence caching, analytics, retrieval, and dashboard-ready outputs.
• Develop SQL and Python data-access logic and assist with APIs, JSON/XML processing, data validation, and automation supporting protocol extraction, historical retrieval, comparison, and source traceability.
• Execute data- and AI-focused testing, including checks for completeness, mapping consistency, retrieval quality, unsupported or hallucinated content, ambiguity, reproducibility, prompt behavior, and regression across approved configurations.
• Document data models, prompts, mappings, test results, interfaces, transformations, implementation decisions, and technical limitations to support client review, knowledge transfer, and iterative Proof of Concept (POC) refinement.
• Works closely with senior data engineers, clinical protocol SMEs, data standards specialists, architects, and AI/prompt engineers to translate approved requirements into working POC components.
• Participates in prompt and LLM testing, technical working sessions, POC demonstrations, validation activities, and iterative refinement…