Principal Engineer - Data Ingestion & AI Pipeline

Job Description

This job is responsible for defining and leading the engineering approach for solutions at the program or portfolio level, to deliver significant business outcomes. Key responsibilities include continuously improving the design, quality, and reuse of the solution and delivering technology enablers that improve development efficiencies for the solution. Job expectations include familiarity with at least one area of engineering, acting as a “go to” reference across the organization, and applying knowledge to improve technical competencies through recruitment and development activities.

Developer Experience (Dev Ex) provides enterprise technical standards and common technical services, platforms, and tools that are leveraged by delivery teams across all lines of business. Within the SDLC Software Delivery Lifecycle program, this role leads portfolio product delivery strategy and execution for enterprise software delivery capabilities, ensuring the right investments, operating model, governance, and prioritization are in place to improve how internal technical users build, test, and deliver software at scale.

The Data Ingestion & AI Pipeline Principal Engineer is responsible for designing and leading the engineering of scalable ingestion pipelines that prepare enterprise data for RAG and AI workloads. This role focuses on extracting, transforming, enriching, validating, chunking, classifying, and loading structured and unstructured data into downstream RAG databases.

This engineer ensures that source data becomes clean, traceable, secure, current, and optimized for retrieval and LLM consumption.

• Develops the engineering approach for the entire program/portfolio solution and works with Architecture, to develop/analyze/deliver the implementation of technical enablers
• Leads the planning, definition, and design of the complex features which span multiple teams and explore solution alternatives
• Creates ideas on designing complex technology and solution development approaches
• Leads the technical oversight for teams in solution development including design reviews and code within own domain
• Defines the technology tool stack for the solution within ranged of internally approved and supported technologies
• Explores state-of-the-art technologies to improve development efficiencies, quality of test/QA coverage, and release management
• Leads and is responsible for the end-to-end test strategy/creation/adherence, and the integration between teams for a program/portfolio solution
• Improve the experience for our developers, making it easier to deliver industry-leading solutions, while managing work efficiently and with the right controls
• Advance our technology platforms through innovation
• Reduce risk and improve quality across our technology portfolio by aligning to a single enterprise architecture strategy and delivering governance that enables consistency, integration and automation
• Design and lead enterprise data ingestion pipelines for structured, semi-structured, and unstructured data.
• Build scalable ingestion patterns for sources such as databases, APIs, documents, PDFs, SharePoint, file shares, data lakes, wikis, ticketing systems, code repositories, emails, and application logs.
• Define transformation patterns for document parsing, text extraction, normalization, deduplication, enrichment, chunking, classification, and metadata generation.
• Establish ingestion standards for source lineage, data freshness, versioning, access controls, and auditability.
• Implement pipeline orchestration, monitoring, retry logic, error handling, and operational dashboards.
• Design incremental ingestion, change detection, delta processing, and reprocessing strategies.
• Partner with RAG database engineers to ensure ingested data is optimized for embedding, indexing, and retrieval.
• Partner with context engineers to ensure data is structured and enriched in ways that support effective LLM reasoning.
• Evaluate and implement OCR, document intelligence, parsing, entity extraction, content classification, and data quality capabilities.
• Define data quality checks for completeness,…