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# IT Technical Project Manager

- **Company:** Lares IT Solutions Inc.
- **Location:** Chicago, IL, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Computer Vision, RAID, Machine Learning, Scrum Methodology, Large Language Models, Model Validation, Generative AI, AI Platforms, Information Technology, Machine Learning Operations
- **Published:** August 22, 2026
- **Apply:** https://www.dice.com/job-detail/3a4ea973-4491-4bda-b9fa-2fd998a63c3d

## About the Role

* 7+ years of technical project/program management experience^.
 * 2+ years specifically managing AI, Machine Learning, Data Science, or Generative AI initiatives^.
 * Proven track record leading multi-team delivery in a matrixed enterprise without relying on direct authority^.
 * Deep experience with Agile, hybrid delivery frameworks, RAID management, and executive communications^.
 * Strong understanding of the AI lifecycle (data readiness, model evaluation, MLOps, deployment, and monitoring)^.
 * Bachelor''s degree in Computer Science, Engineering, Business, or equivalent experience^.

Preferred Qualifications

 * Experience with GenAI, LLMs, RAG, computer vision, or predictive analytics^.
 * Familiarity with cloud AI platforms, APIs, MLOps/LLMOps pipelines, and security controls^.
 * Certifications: PMP, PMI-ACP, SAFe, or Scrum^

## Description

We are seeking a Senior IT Technical Project Manager to lead complex, enterprise artificial intelligence (AI) initiatives across a matrixed environment^. In this role, you will own integrated planning, execution tracking, dependency management, and delivery governance from concept through production readiness^. You will work closely with Data Science, Engineering, Product, QA, and Executive Leadership to drive AI solutions to market using strong influence and technical fluency^., * Execution & Planning: Own end-to-end delivery plans, integrated timelines, critical paths, and dependency management across multiple cross-functional teams^.

 * Quality & Readiness: Orchestrate quality gates, test lifecycle integration, UAT, and production readiness reviews (evaluating data, model, security, and Responsible AI standards)^.
 * Governance & Agile Cadence: Facilitate delivery ceremonies, manage RAID logs, run status reviews, and drive continuous improvement of AI delivery standards^.
 * Cross-Team Alignment: Surface capacity constraints, resolve blockers, and route technical decisions to the appropriate functional leaders^.


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