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Forward Deployed AI Engineer (Remote)

INFT Solutions incUnited States🇺🇸United StatesPosted 26 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
23 hours ago
SQLAWSNLPLLMPythonREST

Job Description





Job Description: Forward Deployed AI Engineer, Intelligent Document Processing and Enterprise Data Matching

Applied AI (NLP, Vision & Edge)

Summary of the Requirement


Strong Eastern/Central Time overlap is required for daily embedded co-build (EBSCO hubs - Ipswich, MA & Birmingham, AL).

Engagement shape: Time-boxed engagements (typ. 4-6 weeks build + hand-off overlap), 2-3 projects running concurrently.

Seniority: Mid-to-senior applied engineers who can build production-quality work and teach it to an owner in parallel.



AI-Driven Invoice Management (AP/AR) - invoice intake and extraction, then validation/matching of line items against EBSCO's Invoice/Product Authority, with human-in-the-loop confirmation.

Federal Bids / Title Authority matching - read an Excel bid/renewal input, fuzzy-match each line against Product Authority (PA within PAVA on the ESOS platform), and auto-populate missing fields (ISSN, product keys, price, offerings).

PAVA price-request automation - the inbound return (publisher price sheet match to authority enrich rates), today manual.

Build the underlying reusable "match-and-enrich against Product Authority" service that all three share.



What you'll do

Co-design and build document-ingestion + entity-matching + enrichment pipelines against a named owner and workflow.

Integrate with enterprise authorities via API, event streams, and extract tables; design human-in the-loop review and exception handling.

Instrument match quality (match rate, precision, manual-touch reduction, error rate) so results are measurable.

Commit all artifacts to EBSCO repos as you go and hand off against a defined independent operation bar.



Required Skills

Intelligent Document Processing - document/structured extraction (OCR and LLM-based), handling messy real-world inputs (Excel, PDF).

Entity resolution / fuzzy matching / record linkage against reference data; data-quality and reconciliation experience.

Strong Python and SQL; data pipelines; REST/API and event-stream integration; cloud (AWS preferred).

Human-in-the-loop workflow design; ability to embed with finance/ops owners and transfer the capability.



Preferred Skills

Prior Intelligent Automation / IDP delivery in finance or operations (AP/AR, subscriptions, contracts).

LLM-assisted extraction and validation; familiarity with master-data / authority systems and enterprise integration.





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