Senior Ai Data Integration Engineer

NorthHill Technology

Mclean, Virginia
30+ days ago

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Skills

Access Controlunmatched
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
Business Solutionsunmatched
Computer Securityunmatched
Debugging Skillsunmatched
IT Governanceunmatched
Identify Issuesunmatched
Information Retrievalunmatched
Information/Data Security (InfoSec)unmatched
Legalunmatched
MCP - Microsoft Certified Professionalunmatched
Machine Toolunmatched
Metadataunmatched
Microsoft Product Familyunmatched
Microsoft SharePointunmatched
Onboardingunmatched
Operations Processesunmatched
Product/Service Launchunmatched
Quality Assuranceunmatched
Quality Managementunmatched
Semantic Searchunmatched
Standards Developmentunmatched
System Integration (SI)unmatched
Traceabilityunmatched
Vendor/Supplier Selectionunmatched
Web Client Plug-insunmatched

Description

NorthHill Technology Resources has an urgent need for a Senior Data Integration Engineer for a cutting-edge opportunity in Mclean, VA. This is a direct-hire role with our client, a highly respected banking organization, It is a hybrid role, with 3 days onsite and 2 remote per week.

Position Summary

Own the bank's approved knowledge and systems layer for AI by implementing secure grounding on enterprise content, approved connectors, permissions-aware retrieval, and DLP-aligned data handling. This role includes the immediate masking and unmasking path for SharePoint-accessed content using Presidio and Protect.

Core Responsibilities

Build and maintain secure grounding patterns for approved content repositories and internal business systems, starting with SharePoint and other governed enterprise sources.
Implement approved connectors and retrieval workflows with permissions-aware access, source traceability, and controls that scope retrieval to the minimum necessary data.
Implement and support Presidio and Protect for immediate masking and unmasking of SharePoint-accessed content before it is released to approved AI workflows.
Partner with Security, IT, Information Governance, and business owners on DLP, sensitivity labels, metadata, redaction, and data-handling controls for AI retrieval paths.
Improve retrieval quality, metadata standards, and integration reliability across structured and unstructured sources so answers remain grounded and supportable.
Create reusable onboarding standards for new content sources, including access review, logging expectations, retention considerations, and validation before activation.
Engineer retrieval services that preserve permissions inheritance and return provenance metadata sufficient to support reviewer verification, citations, and audit traceability.
Build validation checklists for new repositories, connectors, content types, and SharePoint masking flows before they are exposed to employee-facing copilots or higher-risk governed workflows.
Partner with Guardrails and Application teams to tune retrieval quality, reduce hallucination risk, and enforce least-privilege data access across approved workflows.
Support secure integration patterns for approved enterprise AI platforms, including Claude Cowork and related retrieval-dependent tools, where grounding, connector behavior, provenance controls, and masking services must be enforced.

Control Requirements

Implement connector and retrieval logging that supports audit trails for what data sources were accessed, by whom, and under what approved workflow where the platform supports it.
Design integrations to respect data minimization, permissions inheritance, read-only access where required, and restrictions on shared file write or delete behavior.
Help operationalize immediate compensating controls for PII or NPI workflows, including Presidio and Protect for SharePoint-accessed content, with documented fallback redaction controls and QA where needed.
Coordinate evidence and metadata standards so approval artifacts, retrieval traces, and content-source onboarding records can be retained in the governance repository.
Contribute technical review for plugins, custom MCP servers, and other integrations that expose enterprise systems to AI workflows.

Required Qualifications

6+ years in data engineering, integrations, enterprise search, retrieval engineering, knowledge systems, or content-platform engineering.
Hands-on experience with APIs, enterprise content platforms, permissions models, identity-aware retrieval, and reliable integration patterns across heterogeneous data sources.
Strong understanding of data classification, DLP concepts, metadata, lifecycle and retention considerations, and enterprise content governance.
Ability to troubleshoot retrieval quality, indexing, connector reliability, and source traceability in document-heavy environments.
Experience documenting standards so new data sources can be onboarded repeatedly without creating inconsistent control behavior.

Preferred Qualifications and Skills

Experience with SharePoint, Microsoft Graph, Copilot Studio grounding patterns, semantic search, vector or hybrid retrieval, and enterprise content systems used in regulated environments.
Exposure to legal, trust, compliance, HR, or document-heavy operational processes where permissions and provenance matter.
Financial services or other regulated-data experience with practical awareness of privacy, records, and audit obligations.
Hands-on experience with Presidio, Protect, or comparable masking, redaction, and data-protection tooling that can support controlled AI workflows.
Experience supporting Claude Cowork or similar enterprise AI platforms where retrieval, knowledge access, and provenance controls matter.
Familiarity with Claude Code or comparable AI-assisted engineering tools for connector development, debugging, and integration acceleration.

Numbers & Facts

Location

Mclean, Virginia

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