Project Manager – AI Programs

Ampcus Inc.•Mclean, VA

15h•Onsite

About The Position

We are seeking an experienced Project Manager with a strong background in driving AI and machine learning initiatives from concept to deployment. The ideal candidate will have hands-on experience managing cross-functional teams, coordinating data-driven projects, and ensuring the successful delivery of AI-enabled solutions that align with business objectives. This role requires strong leadership, analytical thinking, stakeholder management, and an understanding of modern AI technologies, data pipelines, and product development lifecycles.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Business, or a related field.
5 years of project management experience, with at least 2 years managing AI/ML or data analytics projects.
Strong understanding of: Machine learning workflows, Data engineering concepts, Cloud AI platforms (Azure, AWS, GCP), Model deployment and MLOps practices.
Proven ability to manage cross-functional teams and deliver complex technical projects.
Experience with Agile/Scrum, JIRA, Confluence, or similar tools.
Excellent communication, presentation, and stakeholder management skills.

Nice To Haves

PMP, PMI-ACP, or Scrum Master certification.
Experience with LLMs, generative AI, vector databases, model fine-tuning, or prompt engineering.
Background in industries such as finance, healthcare, retail, or technology.
Familiarity with tools like Databricks, MLflow, Azure Machine Learning, SageMaker, or similar platforms.

Responsibilities

Lead end-to-end planning, execution, and delivery of AI/ML projects, including model development, validation, deployment, and monitoring.
Define project scope, goals, timelines, and success metrics.
Create and maintain detailed project plans, roadmaps, and documentation.
Manage risks, issues, dependencies, and change requests throughout the project lifecycle.
Collaborate with data scientists, ML engineers, software developers, product owners, and business leaders.
Facilitate communication between technical and non-technical teams to ensure clarity and alignment.
Conduct project reviews, sprint planning, and status updates for stakeholders and leadership.
Oversee data ingestion, feature engineering, model training, testing, deployment, and post-production monitoring.
Support the integration of AI models into existing applications or business workflows.
Ensure AI solutions follow compliance, security, and ethical guidelines (e.g., data privacy, fairness, transparency).
Establish best practices for AI project delivery, Agile execution, and model lifecycle management.
Promote continuous improvement and adoption of AI capabilities across the organization.
Ensure alignment with organizational strategy, regulatory requirements, and governance standards.