Implementation Coordinator Jobs

Allocation: 50% project coordination and client delivery; 50% on-premises Document AI solution implementation
Reporting: Project/Account Lead for client delivery; AI Architect/Technical Lead for solution implementation
Location: Albuquerque, NM , with periodic client site visits (10% Travel)

Role purpose

This role has two parts. The first is coordinating client document-processing projects: workload scheduling, client communication, production reporting and delivery reconciliation. The second is turning business and document-processing requirements into clear specifications, then validating the on-premises Document AI solution and supporting its integration, deployment and operational readiness.

The role works closely with the AI Architect, who owns technology selection and architecture, and with the offshore development team, which owns Python application development.

Project coordination and client delivery (50%)

1. Planning and workload management

• Work with client managers to schedule work based on delivery priorities, available capacity and agreed deadlines.
• Keep a delivery tracker covering intake, owners, due dates, dependencies, risks and open issues.
• Coordinate internal resources and production teams so delivery commitments are met.
• Find schedule risks early and propose ways to reduce them.

2. Client communication and governance

• Report project status, delivery progress, delays and any decisions the client needs to make.
• Prepare and send weekly production and delivery reports.
• Hold status meetings and keep meeting notes, action items and decision logs.
• Visit client sites periodically to review each department’s scope, document types, extraction requirements, naming conventions, folder structures and acceptance criteria.

3. Delivery reconciliation and quality

• Reconcile opening backlog and new intake against work that is completed, delivered, rejected, on hold or outstanding.
• Check delivery counts and identifiers, look into missing, duplicate or inconsistent records, and report any discrepancies.
• Keep audit-ready records of what was delivered, when it was accepted and how issues were resolved.

4. Scope and change management

• Keep a register of requirements and change requests.
• Get written agreement from the designated owners before scope or delivery changes take effect.
• Turn approved client requirements into implementation tasks with testable acceptance criteria.

Document AI solution implementation (50%)

1. Requirements and functional specifications

• Gather and document requirements for document intake, classification, extraction, validation, reconciliation, search and reporting.
• Define document types, metadata fields, extraction rules, naming conventions, folder structures and expected outputs.
• Prepare source-to-target mappings, sample input and output datasets, workflow descriptions and acceptance criteria.
• Turn approved requirements into development tasks, answer the development team’s questions, and keep requirements traceable to what gets built.

2. SQL, data validation and reconciliation

• Write SQL queries and approved database routines for validation, reconciliation, exception analysis and reporting.
• Define validation rules for completeness, format, lookups, duplicates and consistency across documents.
• Check processing results against source documents and expected outputs.
• Prepare exception reports with supporting evidence and track each issue until it is resolved.

3. Integration testing and solution quality

• Test the document-processing workflows, APIs, database outputs and integrations the development team delivers.
• Build representative test datasets that cover document variations, poor OCR quality, missing information, duplicates and conflicting values.
• Score extraction and retrieval results against agreed reference answers, and confirm that outputs keep source-document and page references.
• Test retries, reprocessing, interrupted jobs and human-review workflows.
• Log defects so they can be reproduced, coordinate the fixes, and confirm the corrected behavior.

4. On-premises deployment and operational support

• Support environment setup and deployment, following the architecture and procedures the AI Architect has approved.
• Coordinate installation prerequisites, configuration, database connectivity, internal endpoints and access requirements.
• Run deployment checklists, check service health and confirm processing works end to end, including offline operation where required.
• Monitor processing, review logs, investigate failures and escalate issues as needed.
• Maintain configuration records, operating procedures, troubleshooting guides and release checklists.

5. Development coordination and user acceptance

• Manage the implementation backlog, priorities and dependencies with the offshore development team, and report progress against milestones.
• Run solution demonstrations and user acceptance testing (UAT).
• Record user feedback and separate defects from new requirements.
• Prepare release-readiness evidence for sign-off, and provide user training and operational handover.

Qualifications (suggested)

• Bachelor’s degree in Information Systems, Computer Science, Engineering or a related field.
• 4+ years of combined experience in project coordination and technical implementation, preferably in document management, ECM or data processing.
• Strong SQL skills and experience with data validation and reconciliation.
• Familiarity with OCR, document classification, data extraction and AI/ML-based document processing.
• Experience working with offshore development teams and running UAT.
• Excellent written and verbal communication skills, with experience in client-facing roles.
• PMP, CAPM or Agile certification is a plus.

Pay: $20.00 - $30.00 per hour

Expected hours: 30.0 – 40.0 per week

Work Location: In person