Technical Project Manager Job Irving area,Texas USA,IT/Tech

Bachelor's or Master's degree in Computer Science, Engineering, Business, or a related field.
7+ years of experience in technical project management, with a minimum of 3 years managing AI/ML projects.
Requires a blend of strong project management acumen, technical understanding, exceptional communication skills, and the ability to navigate complex organizational structures to drive successful, ethical, and compliant AI solutions.
Thorough understanding and proven experience with AI governance frameworks, ethical AI principles, and regulatory compliance specific to the financial services industry.
Strong experience working in Agile environments, including serving as a Scrum Master.
Demonstrated ability to plan, track, and deliver complex technical projects on time and within budget.
Excellent written and verbal communication skills, with the ability to articulate complex technical concepts and project statuses to diverse audiences, including senior leadership.
Proven ability to coordinate and communicate with various stakeholders (technical, business, legal, compliance) to achieve project objectives and secure approvals.
Strong technical aptitude, capable of conversing effectively with technical teams and understanding architectural decisions and challenges.
Exceptional problem-solving, conflict resolution, and negotiation skills.
Highly accountable, committed, and possesses a growth mindset, continuously seeking to learn and improve.

What You Will Be Doing

Project Leadership & Management:
Lead and manage multiple technical AI projects, ensuring they are delivered on time, within scope, and within budget. This includes defining project scope, goals, deliverables, and resource requirements.
AI Governance & Responsible AI Compliance:
Drive the integration of AI governance and Responsible AI principles throughout the project lifecycle. Ensure all AI development adheres to established ethical guidelines, regulatory requirements, and internal policies, especially relevant to financial firms.
Documentation & Approval Management:
Coordinate the creation and maintenance of necessary supporting documentation for AI projects, facilitating communication and collaboration to secure all required internal and external approvals (e.g., legal, compliance, risk, architecture).
Planning, Execution & Delivery:
Develop comprehensive project plans, track project progress against milestones, manage risks and dependencies, and ensure successful execution and delivery of AI solutions.
Agile and Scrum Master Responsibilities:
Work effectively within an Agile development environment, acting as a Scrum Master when needed. Facilitate sprint planning, daily stand-ups, reviews, and retrospectives, removing impediments and fostering a collaborative team environment.
Technical Team Communication:
Serve as the primary liaison between business stakeholders and technical development teams (data scientists, ML engineers, software developers), translating business requirements into technical tasks and ensuring mutual understanding.
Stakeholder Communication & Reporting:
Provide clear, concise, and timely status updates, executive summaries, and recommendations to senior leadership, project sponsors, and other key stakeholders. Tailor communication to different audiences, highlighting critical information and potential impacts.
Conflict Resolution:
Proactively identify, address, and resolve project conflicts, impediments, and interpersonal issues, ensuring project momentum and maintaining positive team dynamics.
Accountability & Commitment:
Demonstrate a high level of accountability for project outcomes and a strong commitment to achieving business objectives while upholding responsible AI principles.
Forward Thinking & Driving Priorities:
Exhibit a growth mindset by continuously seeking opportunities for improvement, anticipating future challenges, and actively driving strategic priorities within the AI landscape.
ractices.
Provide technical leadership and mentorship to development teams globally.
Review system designs and code to ensure alignment with enterprise architecture and engineering standards.
Collaborate with business stakeholders, risk partners, and technology leadership to define strategic technology solutions.
Assess technology risks, identify control gaps, and ensure compliance with enterprise technology policies and regulatory expectations.
Support production stability, performance optimization, and platform modernization initiatives.