MCO (MyComplianceOffice)
Website:
mco.mycomplianceoffice.com
Company:
https://www.linkedin.com/company/mycomplianceoffice
Seniority: Not Applicable
Industries: Capital Markets
Job details:
Job Description
About the Role As a Product Owner on MCO’s eComms Compliance team, you will own the roadmap for a new scrum team dedicated to AI feature development across our communications surveillance and archiving solutions, which serve compliance professionals at global financial services firms including banks, broker-dealers, hedge funds, insurance companies, and RIAs.
This role will focus on AI-powered capabilities—including AI-based risk detection, message and conversation summarization, and AI-assisted archive search—core to helping regulated institutions surface, investigate, and evidence communication risk at scale. You will be responsible for defining product requirements, prioritizing feature development, and working closely with cross-functional teams to deliver high-quality software solutions in a fast-paced SaaS environment.
You’ll work at the intersection of regulatory needs and emerging AI capabilities, helping MCO deliver market-leading tools that simplify complex compliance challenges.
Job Requirements
Experiences and Skills:
- 8 to 12 years of overall IT experience, including at least 5 years of proven experience in Product Management, Product Ownership, or a similar role within SaaS-based or enterprise B2B environments.
- Proven success managing features or products built on AI/ML capabilities—such as LLM-based summarization, classification, risk scoring, semantic or vector search, or anomaly detection.
- Experience with compliance or regulatory technology and familiarity with financial services industries such as banking, broker-dealers, hedge funds, insurance, or RIAs.
- Hands-on experience working with data-rich applications and large volumes of unstructured or sensitive data.
- Hands-on experience shipping AI-powered features using large language models (LLMs), natural language processing (NLP), retrieval-augmented generation (RAG), or other applied machine learning systems.
- Demonstrated ability to define and deliver features that drive data extraction, normalization, reporting, and advanced user insights.
- Comfortable translating complex business and technical needs into actionable user stories and product requirements.
- Track record of collaboration within globally distributed teams across multiple time zones.
- Strong communicator and cross-functional collaborator, able to align stakeholders from engineering, compliance, design, support, and customer success.
- Proficient with agile tools and methodologies (e.g., Jira, Confluence, Scrum or Kanban practices).
- Bachelor’s degree required; a degree in business, computer science, engineering, or a related technical field is preferred.
Responsibilities
Job Responsibilities
- Own and manage the product backlog for AI-driven features, including risk detection, message summarization, and AI-assisted archive search.
- Translate high-level customer and business needs into clear, actionable user stories and acceptance criteria.
- Collaborate with engineers, designers, QA, and other stakeholders to deliver high-quality product increments.
- Drive product discovery and user research to deeply understand compliance professionals’ workflows and pain points.
- Define success criteria for AI features—precision, recall, false-positive rates, and latency—and partner with data science and engineering to evaluate model performance before release.
- Work with Legal, Compliance, and Information Security to ensure responsible AI practices—data privacy, explainability, auditability, and human-in-the-loop review—are built into each feature.
- Partner with stakeholders across Product, Sales, Customer Experience, and Support to prioritize roadmaps and ensure alignment.
- Act as the voice of the customer, advocating for usability, performance, and compliance use cases.
- Monitor industry trends, competitive offerings, and regulatory developments to inform product direction.
- Ensure releases meet quality and performance standards, and support go-to-market efforts with product documentation and enablement.
- Collaborate on metrics and reporting to assess product success and adoption.
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