What are the responsibilities and job description for the Senior Project Manager / AI Software Rollout position at WSN?
We are seeking a results-driven and technically fluent Senior Project Manager to lead the end-to-end rollout of enterprise-grade Artificial Intelligence (AI) and machine learning software solutions. Based in our New York office, you will sit at the intersection of business strategy and cutting-edge engineering, guiding cross-functional teams through the deployment of transformative AI initiatives.
If you thrive in complex, high-stakes environments and have a proven track record of taking complex AI products from pilot to production, we want to hear from you.
Key Responsibilities
- End-to-End Project Delivery: Own the full project lifecycle for AI/ML software implementations, defining scope, milestones, resource allocation, and rigorous delivery timelines.
- Cross-Functional Leadership: Partner closely with data scientists, ML engineers, product managers, security/compliance teams, and executive stakeholders to align technical execution with strategic business goals.
- Risk & Governance Management: Proactively identify and mitigate risks related to model drift, data privacy, regulatory compliance, change management, and technical debt.
- Stakeholder Enablement & Change Management: Translate complex technical concepts into clear business narratives for executive leadership. Drive user adoption and change management strategies across business units.
- Agile Governance: Facilitate Agile ceremonies, manage backlogs, track velocity, and remove blockers to ensure continuous and predictable software delivery.
- Vendor & Partner Oversight: Manage relationships with external software vendors, consultants, and cloud infrastructure partners as needed.
Key Requirements & Qualifications
- Experience: 5 years of technical project management experience, with a minimum of 3 years dedicated to managing the rollout of AI, Generative AI, or ML software solutions in enterprise environments.
- Domain Expertise: Experience within Financial Services, Banking, or Insurance sectors is a major plus, particularly regarding compliance frameworks, data governance, and secure cloud architectures.
- Technical Fluency: A solid understanding of the AI/ML lifecycle (data ingestion, model training, validation, deployment, and monitoring) and familiarity with modern MLOps pipelines and cloud platforms (AWS, Azure, or GCP).
- Methodologies: Mastery of Agile/Scrum methodologies; PFM, CSM, or PMP certifications are highly desirable.
- Communication: Exceptional stakeholder management, facilitation, and executive-level communication skills, with a proven ability to bridge the gap between technical teams and business units.
- Education: Bachelor’s degree in Computer Science, Engineering, Business Administration, or a related field (Master’s preferred).