Product Manager

Lumen Dynamics AI is the leading enterprise Agentic AI solution for middle and back-office automation. The company delivers production-ready AI agents that automate reconciliation, exception resolution, and oversight workflows for the world's largest asset managers, fund administrators and managed service providers. Lumen Dynamics ' agentic AI architecture enables fully autonomous processing of complex middle and back-office workflows while maintaining the transparency, control, and auditability required by global financial institutions. Clients rely on Lumen Dynamics to deliver measurable operational efficiency and accuracy improvements across mission critical processes. We are seeking a talented and motivated Product Manager to join our rapidly growing team. You'll work alongside a team that's redefining what's possible in capital markets technology, while collaborating closely with leadership in a fast-moving, high-agency environment. The Opportunity As Product Manager, you will sit at the intersection of financial expertise, artificial intelligence, and disciplined execution. This is a "player-coach" style role that requires both high-level product strategy and hands-on project management. This is a high-impact role where you will combine deep financial intuition with disciplined technical execution. You will be the bridge between complex global regulations and the code that automates them. You will be responsible for defining the future of AI-driven financial oversight while ensuring that our development cycles are predictable and high-quality. You must understand the nuances of institutional finance to ensure our products are solving the industry’s most pressing challenges. Key Responsibilities Product Strategy & Financial Services Domain Leadership Vision & Roadmap: Define the long-term strategy for one or more product areas, ensuring it evolves ahead of shifting global financial regulations (e.g., SEC, FCA, ESMA). Domain Expertise: Act as the internal subject matter expert on financial workflows, ensuring the AI models are solving for the right "edge cases" in financial data. KPI Management: Establish and track product success metrics centered on operational efficiency, risk reduction, and ROI for institutional clients. Project Management & Execution Delivery Management: Own the end-to-end delivery lifecycle. You aren't just defining the "What"; you are managing the "When" by building sprint plans, managing backlogs, and removing technical blockers. Requirement Architecture: Translate complex financial requirements into detailed PRDs, user stories, and acceptance criteria that Engineering and Data Science teams can execute upon. Cross-Functional Sync: Lead the "rhythm of the business": sprint planning, stand-ups, and retrospectives, ensuring Engineering, Design, and QA are aligned on high-stakes deadlines. Stakeholder & Risk Management Risk Mitigation: Identify potential project risks (data gaps, technical debt, scope creep) early and implement mitigation strategies to maintain momentum. Client Alignment: Partner with Sales and Customer Success to ensure product launches are seamless and that internal teams are equipped with the technical knowledge to support global FS clients. What We’re Looking For Required Experience Domain Expertise: 5+ years of experience in Financial Services, FinTech, or RegTech. You should be deeply familiar with institutional finance operations (e.g., Asset Management, Fund Accounting, or Regulatory Reporting). Product Lifecycle Management: Proven track record of taking complex data products from initial concept through to successful market launch. Hands-on Project Management: Experience managing technical workstreams using Agile/Scrum methodologies. You should be comfortable using Jira, Confluence, or similar tools to track velocity and capacity. Data Literacy: Ability to work closely with Data Scientists. You don’t need to code, but you must understand how data inputs, model training, and output validation impact the final financial product. Communication: Exceptional ability to explain complex technical or financial concepts to both engineers and C-suite executives. Preferred Qualifications Advanced Certifications: CFA, FRM, or PMP certifications are highly desirable. AI/ML Familiarity: Experience with machine learning products, specifically regarding "Explainable AI" within a regulated environment. Technical Background: A degree in Finance, Computer Science, Mathematics, or a related field, or prior experience in a technical role. Big Data Experience: Familiarity with SQL, Snowflake, Databricks, or other large-scale financial data warehousing. Why You Should Join Us This is a high-impact opportunity to build the autonomous infrastructure for middle and back-office automation while working alongside a team redefining what’s possible in capital markets. We offer competitive compensation, comprehensive benefits, and professional development support as you help us build the future of financial