Unstructured Data Engineer

Description

The Leidos Digital Modernization Sector is seeking an Unstructured Data Engineer; this position will allow for full time telework from any U.S. based location

POSITION SUMMARY:
We are seeking a highly skilled and innovative Unstructured Data Engineer to lead the design, implementation, and operationalization of unstructured data pipelines supporting Retrieval-Augmented Generation (RAG) and enterprise AI initiatives. This role will serve as the technical expert responsible for transforming raw, unstructured content into trusted, governed, AI-ready data products.
The ideal candidate has deep experience in RAG architectures, document preprocessing, metadata enrichment, vectorization, and embedding workflows, and understands how to operationalize these capabilities at enterprise scale. Experience with Ohalo Data xRay or similar unstructured data processing platforms is strongly preferred.

PRIMARY RESPONSIBILITIES:

• Design, build, and manage end-to-end RAG pipelines for enterprise AI applications.
• Lead preprocessing of unstructured data, including discovery, classification, cleansing, redaction, and metadata enrichment.
• Develop and optimize document chunking, embedding, and vectorization strategies for structured and unstructured datasets.
• Coordinate ingestion of curated datasets into vector databases and AI platforms.
• Package curated unstructured datasets as governed, reusable data products for enterprise consumption.
• Define and implement metadata tagging strategies to align with Collibra governance standards.
• Partner with Data Governance and Data Quality teams to ensure AI-ready data meets enterprise standards for lineage, classification, and compliance.
• Evaluate and optimize embedding models, retrieval strategies, and indexing performance.
• Monitor and tune RAG pipeline performance, including latency, retrieval accuracy, and cost efficiency.
• Implement automation for document ingestion, transformation, and publishing workflows.
• Support integration with enterprise AI platforms (e.g., ChatGPT Enterprise, AskSage, Moveworks).
• Conduct cost analysis and capacity planning for vector storage and processing workloads.
• Provide technical guidance on AI data readiness and unstructured data lifecycle management.
• Design, implement, and optimize enterprise-grade RAG and prompt engineering frameworks, including context engineering strategies (chunking, metadata enrichment, semantic filtering, dynamic context management) to improve retrieval accuracy, grounding, and response quality.
• Develop and maintain scalable multi-modal data pipelines that ingest, preprocess, embed, and integrate text, documents, images, audio, and structured data into governed vectorized data products consumable by enterprise AI platforms.

BASIC QUALIFICATIONS:

• Bachelor's degree in Computer Science, Data Engineering, AI/ML, or related field and 8+ years of relevant experience.
• Hands-on experience designing and implementing RAG architectures in production environments.
• Experience working with unstructured data (PDFs, documents, email, transcripts, images with OCR, etc.).
• Strong proficiency in Python and experience with NLP/LLM frameworks (e.g., LangChain, LlamaIndex, Hugging Face, OpenAI APIs).
• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch, Azure AI Search).
• Experience implementing document chunking, embedding generation, and similarity search.
• Understanding of metadata modeling and governance principles.
• Experience building scalable data pipelines in cloud environments (AWS, Azure, or GCP).
• Hands-on experience with prompt engineering, evaluation metrics, and context window optimization.
• Strong understanding of multi-modal data processing and pipeline engineering.
• Strong knowledge of API integration and microservices architecture.
• US Citizenship is required.

PREFERRED QUALIFICATIONS:

• Experience with Ohalo Data xRay or similar unstructured data discovery and redaction platforms.
• Experience aligning RAG pipelines with enterprise Data Governance frameworks (e.g., Collibra).
• Familiarity with data classification, CUI/PII handling, and redaction controls.
• Experience packaging datasets as governed data products with defined SLAs and stewardship.
• Experience integrating AI-ready datasets into enterprise tools such as ChatGPT Enterprise, AskSage, or similar AI copilots.
• Understanding of model evaluation metrics for retrieval quality (precision, recall, MRR, hallucination reduction).
• Experience working in regulated or government environments.
• Familiarity with MLOps practices and AI lifecycle management.
• Experience optimizing infrastructure costs for embedding and vector storage workloads.
• Awareness of AI/ML lifecycle management practices, including model evaluation, monitoring, versioning, governance, and responsible AI considerations in production environments.
• Familiarity with Model Context Protocol (MCP) concepts and agentic architectures, including tool orchestration, memory management, and multi-step reasoning workflows.
• Exposure to Knowledge Graph and graph database technologies (e.g., Neo4j, RDF/SPARQL, property graphs) and their application in semantic search, entity resolution, and AI context enhancement.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

About Leidos

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit www.Leidos.com.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits.

Securing Your Data

Beware of fake employment opportunities using Leidos' name. Leidos will never ask you to provide payment-related information during any part of the employment application process (i.e., ask you for money), nor will Leidos ever advance money as part of the hiring process (i.e., send you a check or money order before doing any work). Further, Leidos will only communicate with you through emails that are generated by the Leidos.com automated system - never from free commercial services (e.g., Gmail, Yahoo, Hotmail) or via WhatsApp, Telegram, etc. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com.

If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.

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