AI Deployment - Project Lead

Galorath Federal

Project Lead - AI Platform Deployment

Galorath is an Employee-Owned Company - Be a Part of an exciting industry leading organization with Galorath's competitive Employee Stock Ownership Plan (ESOP) offered to all employees at no cost.

Location: Fairfax, VA 

The Project Lead is responsible for the successful delivery of the AI platform deployment consulting engagement, ensuring seamless coordination between the consulting team and the AI product development team.

This individual will manage all aspects of the project lifecycle, from initiation and planning through deployment and training, with a focus on meeting client objectives and ensuring alignment between technical and business goals. The role emphasizes the strategic implementation of AI technologies to transform business operations and achieve measurable improvements.

Key Responsibilities

1. Project Initiation and Planning

Lead Project Kickoff (R: Accountable):

• Organize and conduct the kickoff meeting with stakeholders.
• Define objectives, scope, deliverables, and governance structure in collaboration with both teams.
• Establish communication protocols to ensure smooth interactions across teams.

Develop and Oversee the Project Plan (R: Responsible):

• Draft the project management plan, including timelines, budgets, and resource allocations.
• Identify risks and develop mitigation strategies in consultation with both teams.
• Define success metrics and acceptance criteria, ensuring alignment with client expectations.

2. Use Case Discovery and Analysis

Facilitate Business Needs Assessment (R: Responsible):

• Lead workshops and interviews with client stakeholders to uncover pain points and operational inefficiencies.
• Work with the consulting team to gather data requirements and evaluate the client’s existing infrastructure.

Guide Use Case Identification (R: Responsible):

• Brainstorm potential AI use cases with client and consulting team inputs.
• Prioritize use cases based on feasibility, ROI, and alignment with business goals.
• Ensure the documentation of finalized use cases is clear and actionable for the AI product development team.

Oversee Data Assessment and Preparation (R: Accountable):

• Coordinate the assessment of data availability, quality, and compliance requirements.
• Work with both teams to identify and resolve data gaps and ensure privacy and security measures are in place.

3. AI Platform Deployment and Integration

Oversee Platform Configuration and Customization (R: Accountable):

• Ensure the AI product development team installs, configures, and customizes the platform based on identified use cases.
• Validate initial configurations with sample data in consultation with both teams.

Manage System Integration (R: Accountable):

• Facilitate collaboration between consulting and development teams to integrate the AI platform with the client’s IT systems.
• Monitor the development of APIs or middleware and ensure end-to-end system testing meets project requirements.

Supervise Deployment and Training (R: Accountable):

• Oversee the deployment of the AI platform into the production environment.
• Coordinate end-user training sessions, ensuring the consulting team provides user guides and support materials.
• Collect feedback post-deployment and guide refinement of the platform’s configuration.

4. Business Process Reengineering

Conduct Advisory and Consultative Business Process Reengineering (R: Responsible):

• Analyze current business processes to identify inefficiencies and areas for improvement.
• Collaborate with client stakeholders to design optimized workflows that leverage the AI platform’s capabilities.
• Provide actionable recommendations to align business processes with strategic objectives and maximize ROI.
• Facilitate the implementation of redesigned processes, ensuring alignment with organizational goals and technical requirements.

5. Client Relationship Management

Foster Strong Client Relationships (R: Accountable):

• Build and maintain trust with clients, ensuring alignment with their strategic objectives.
• Act as a key advisor, addressing concerns and providing insights into best practices for AI implementation.
• Offer post-deployment support to ensure sustained client success and satisfaction.

6. Innovation and Continuous Improvement

Promote Innovation (R: Responsible):

• Stay informed on emerging AI trends and propose innovative solutions to enhance client outcomes.
• Identify opportunities to expand or refine the AI platform’s capabilities during and after deployment.

7. Change Management

Facilitate Organizational Change (R: Responsible):

• Develop and implement strategies to drive user adoption of AI technologies.
• Address resistance to change by communicating benefits and providing support during the transition.

8. Compliance and Ethical Considerations

Ensure Compliance and Ethics (R: Accountable):

• Adhere to industry standards, data privacy regulations, and ethical AI practices.
• Collaborate with legal and compliance teams to mitigate risks associated with AI implementation.

9. Metrics and Reporting

Establish Metrics and Reporting (R: Responsible):

• Develop dashboards and regular progress reports for stakeholders.
• Track AI performance metrics and report on measurable business impacts.

10. Scalability and Futureproofing

Design for Scalability (R: Responsible):

• Ensure AI solutions are scalable and adaptable to evolving client needs.
• Plan for future enhancements to align with organizational growth.

11. Training and Development

Upskill Client Teams (R: Responsible):

• Develop training materials and resources to empower client teams.
• Conduct workshops to ensure clients can sustain and optimize AI platform usage.

Integrated Skills and Competencies

Project Management:

• Maintain accountability for task execution across the WBS tasks while aligning with the RACI roles.
• Monitor progress for tasks such as risk identification, stakeholder communication, and defining success metrics.

Leadership and Communication:

• Act as the primary liaison between stakeholders, ensuring both the consulting and product teams are aligned on their responsibilities (e.g., consulting team driving discovery tasks; product team managing technical tasks).

Technical and Business Acumen:

• Balance the consulting team’s focus on business strategy with the product team’s expertise in platform configuration and integration.

Analytical Skills:

• Utilize data analytics and AI performance metrics to inform strategic decisions and measure project success.

AI-Specific Expertise:

• Apply knowledge of machine learning models, natural language processing, and predictive analytics to meet client objectives.

Soft Skills:

• Exhibit adaptability, resilience, and an ability to navigate ambiguous project environments.

EEO/AA including individuals with disabilities and veterans