Technical Product Manager

Comun•New York, NY

About The Position

At Común, the Technical Product Manager is the architect behind how our customer experience scales. This isn’t a traditional Product role, it’s a systems-builder and people-leader position at the intersection of product, operations, data, engineering, automation, and strategy. You’ll design the workflows, tools, and feedback loops that transform complex, human-heavy processes into simple, intelligent systems — enabling us to serve millions of immigrant families with the quality, trust, and empathy they deserve. You’ll be deeply embedded within the Customer Success organization, while operating as a true extension of Product and Engineering. You’ll identify friction across the customer journey, translate operational pain points into product improvements, and deploy AI-driven automations that make our support faster, smarter, and increasingly proactive. As Común grows, this role has the opportunity to lead and develop a small, high-impact team, setting the vision for how AI-augmented operations function across the company. This is a high-leverage, highly cross-functional role: you’ll partner closely with leaders across Product, Data, Engineering, Operations, Compliance, and Customer Success to build the operational foundation that keeps Común efficient, compliant, and deeply human as we scale. If you’re equal parts builder and manager, someone who thrives in ambiguity, sees systems where others see chaos, and wants to apply AI and product thinking to one of the most mission-driven fintechs in the U.S. - this role is for you!

Requirements

5–8+ years of experience in Product Operations, BizOps, Technical Program Management, Product Management, or similar roles at a tech company or startup
Proven ability to build, automate, or scale workflows using AI tools, APIs, or low-/no-code platforms
Hands-on experience with SQL, data modeling, and analytics stacks (Snowflake, DBT, Fivetran, or similar)
Comfort prototyping with Python, JavaScript, or automation platforms
Practical experience working with LLMs or agent architectures — you’ve built or shipped an internal AI tool, chatbot, or automation
Strong collaboration skills with Product and Engineering, including writing technical specs and driving initiatives end-to-end
Leadership and stakeholder management skills — you can influence prioritization, drive consensus, and operate effectively in resource-constrained environments
A systems thinker who loves simplifying complexity, automating processes, and measuring impact
High empathy, low ego, and a strong bias toward action
Bachelor’s degree in a quantitative field (economics, statistics, management, or related), or equivalent experience in data-driven roles
6+ years of experience in Business Operations, Product Operations, Product Management, Strategy, or similar roles
Experience leading technical and AI-driven projects in partnership with engineering teams
Experience in a fast-growing startup environment
Demonstrated success leading cross-functional, strategic initiatives
Based in or willing to relocate to New York
A genuine interest in serving an underserved community

Nice To Haves

Experience in fintech, payments, or regulated environments
Knowledge of customer journey analytics and lifecycle automation
Familiarity with compliance, KYC, or customer verification workflows
Experience with internal tools like Supabase, Retool, or Airflow
Comfort designing or integrating AI copilots to support internal teams
Spanish-speaking preferred

Responsibilities

Build & Scale Intelligent Systems
Architect scalable operations platforms: Identify, design, and automate manual workflows across onboarding, support, and lifecycle management using AI, internal tools, and system integrations.
Build AI-powered agents and workflows: Prototype and deploy automations using tools like OpenAI, LangChain, Zapier, or n8n to replace repetitive human work and unlock scale.
Lead Through Influence (and Eventually People)
Own and evolve a critical function: Set the strategy for technical operations and customer systems, with the opportunity to lead and grow a team over time.
Drive alignment across teams: Act as the connective tissue between Customer Success, Product, Engineering, Data, and Operations — ensuring priorities are clear and execution is tight.
Turn Insight into Product Impact
Diagnose customer bottlenecks: Analyze customer journeys, funnel data, and support interactions to uncover friction that impacts activation, funding, or retention.
Bridge product and operations: Partner with Product Managers and Engineers to translate operational pain points into product features, backend improvements, or new platform capabilities.
Own data instrumentation and insights: Design data models and dashboards using Snowflake, DBT, Fivetran, or similar tools to drive smarter decisions.
Create Continuous Feedback Loops
Implement scalable learning systems: Convert customer data, agent feedback, and operational metrics into automated alerts, experiments, and improvements.
Ship, test, iterate: Move fast, test hypotheses, measure outcomes, and refine — applying strong product thinking to operations and customer experience.