Description:
Eisner Amper is seeking a highly motivated and experienced Project Manager to oversee the planning, coordination, and execution of AI-driven initiatives across Eisner Amper’s enterprise platform. This role bridges business strategy and technology execution—managing complex, cross-functional projects that span data engineering, model development, automation, and product delivery.
You’ll be responsible for translating strategic goals into actionable project plans, managing Agile delivery teams, and ensuring alignment between business, technical, and compliance stakeholders. The ideal candidate thrives in environments where innovation meets rigor—able to balance experimentation with governance, and speed with precision.
Strong organization, communication, and influencing skills, along with change management, business acumen, managing multiple priorities and experience with systems implementations are vital for this role.
What it Means to Work for EisnerAmper:
- You will get to be part of one of the largest and fastest growing accounting and advisory firms in the industry
- You will have the flexibility to manage your days in support of our commitment to work/life balance
- You will join a culture that has received multiple top “Places to Work” awards
- We believe that great work is accomplished when cultures, ideas and experiences come together to create innovative solutions
- We understand that embracing our differences is what unites us as a team and strengthens our foundation
- Showing up authentically is how we, both as professionals and a Firm, find inspiration to do our best work
What Work You Will be Responsible For:
Project Leadership
- Lead end-to-end delivery of AI and automation projects across the EisnerAI portfolio, ensuring on-time, on-budget, and high-quality outcomes.
- Define and manage project scope, timelines, milestones, and dependencies in collaboration with product owners, engineers, and data scientists.
- Drive sprint planning, standups, retrospectives and support backlog refinement in partnership with product and technical leads.
- Coordinate cross-functional collaboration across technology, service lines, and operations teams.
Technical Execution
- Oversee delivery of AI and data components such as model pipelines, APIs, data integrations, and user-facing applications built on Azure AI and Microsoft ecosystem tools.
- Partner with engineering leads to monitor sprint velocity, manage technical risks, and enforce DevOps, security, and responsible AI standards.
- Translate business and compliance requirements into technical deliverables, ensuring adherence to data privacy, security, and governance frameworks (NIST AI RMF, Reg 7216, PCAOB).
- Collaborate with internal and external partners to align project milestones, integration timelines, and resource needs.
Stakeholder Management
- Serve as a central point of contact for technical and non-technical stakeholders.
- Coordinate executive-ready reporting on project health, risks, and dependencies.
- Support change management, training, and adoption planning for new AI capabilities.
- Foster a culture of transparency, accountability, and continuous improvement across delivery teams.
Basic Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
- 6+ years of experience managing technology projects, including at least 2+ years in AI, data, or software development environments.
Preferred Or Desired Qualifications
- Demonstrated success managing Agile delivery teams and working within iterative development lifecycles.
- Experience with Azure DevOps or similar Agile tools (e.g., Jira, GitHub, Confluence).
- Familiarity with cloud architectures (Azure preferred), APIs, and data pipeline concepts.
- Strong understanding of software development lifecycle (SDLC), MLOps, and QA/testing practices.
- Excellent communication, organization, and stakeholder management skills.
- Ability to translate technical concepts for non-technical audiences.
- PMP, CSM, or equivalent Agile/PM certification.
- Experience with Microsoft Azure AI, ML Studio, or OpenAI services.
- Exposure to data governance, AI risk management, or responsible AI frameworks.
- Prior experience in professional services or enterprise technology transformation programs.