Kovo

• Own the strategy and roadmap for the full customer journey - activation, engagement, retention, referral, and reactivation - across in-product experiences and lifecycle messaging (email, push, in-app, sms) • Define the north star and input metrics for growth and lifecycle, and continuously optimize for measurable, incremental impact on revenue, retention, and LTV • Partner with Engineering, Design, and Marketing to ship growth and lifecycle work as first-class product investments, not one-off campaigns • Identify and prioritize the highest-leverage opportunities across the funnel, sequencing bets between in-product changes, lifecycle programs, and acquisition/conversion surfaces • Audit and evolve existing lifecycle programs across email, push, in-app, and sms messaging - to improve onboarding, engagement, retention, cross-sell, and reactivation • Design and scale event-driven, behavior-triggered lifecycle programs tightly integrated with product events and user state • Build and maintain a modular email design system / component library, leveraging AI tools to increase speed and quality • Define segmentation and personalization strategy across the lifecycle, grounded in user behavior and predicted value • Own conversion rate optimization across web/app acquisition flows, onboarding, lifecycle messaging, and key in-product moments • Define the experimentation framework: hypothesis generation, prioritization, test design, sample sizing, readouts, and documented learnings • Build a durable backlog of growth experiments and ensure learnings compound across the team • Explore and ship AI-powered workflows and proactive messaging agents to improve personalization, cross-sell, product discovery, and re-engagement • Use AI to accelerate research, segmentation, copywriting, creative iteration, and analysis - treating it as a core capability, not a buzzword • Push the boundaries of what a small growth and lifecycle team can do when AI is deeply embedded in the workflow • Partner closely with Product and Engineering to ensure growth and lifecycle work is treated as core product surface area • Work with Engineering to instrument events cleanly, define metrics, and build the analytics foundation the function needs • Coordinate with Design, CX, and Marketing on messaging, brand consistency, and customer-facing voice

Role Description Join us as a Backend Engineer to build and scale the infrastructure that powers financial access for millions of underserved Americans. This role is for you if you want to own critical systems end-to-end and care deeply about performance, reliability, and scalability. You'll be expected to aggressively leverage AI-assisted development tools to dramatically accelerate your output and maximize impact, all while maintaining strong code quality and system reliability. Qualifications - Systems-oriented mindset - Care deeply about performance, reliability, and scalability - Motivated by ownership and accountability for system outcomes - Think critically about architectural decisions and their long-term implications - Thrive in ambiguity and are comfortable making technical decisions with incomplete information - Self-starter who can work independently and drive projects to completion - Focused on shipping high-quality systems fast - Comfortable in a high-intensity role and seeking an ambitious workload - Strong sense of ownership and willingness to deliver on tight deadlines - Believe software engineering is evolving from writing code to orchestrating AI agents - Embrace AI generation of code and workflow improvements while maintaining high quality - Hate AI slop and care about code quality and system reliability Requirements - 5+ years or equivalent depth of experience in professional software engineering, with significant backend focus - Experience building and scaling production systems with Node and AWS - Proficient with TypeScript (bonus) - Track record of delivering reliable, performant systems at scale Benefits - Direct impact on millions of people’s ability to access credit - High ownership with minimal bureaucracy - Speed, learning, and impact are core values

• Own and evolve Kovo’s lifecycle marketing strategy across email, push notifications, and in-app messaging. • Audit and optimize existing lifecycle programs, identifying opportunities to improve activation, engagement, retention, and long-term customer value. • Design and scale event-driven lifecycle programs to support personalized, behavioral-triggered messaging. • Build and maintain a modular email design system/library, leveraging AI tools to increase speed and quality. • Partner with Product and Data to ensure lifecycle messaging is tightly integrated with product events and user behavior. • Own conversion rate optimization: define the experimentation framework, prioritize and sequence tests across lifecycle messaging and web conversion flows, and document learnings. • Explore and implement AI-powered workflows and proactive messaging agents to improve personalization, cross-sell, and product discovery. We believe AI fundamentally changes what a small lifecycle team can do - you'll have the mandate and resources to prove that out. • Define lifecycle KPIs and continuously optimize for measurable performance improvements.

• Own the full design process: from research and discovery through wireframes, prototypes, and polished UI • Design intuitive, accessible, and visually compelling experiences that translate complex financial problems into clear user flows • Evolve our design system to ensure consistency and scalability across the product • Use data, user research, and experimentation to continuously validate and improve designs • Apply AI to supercharge upfront research, competitive analysis, and rapid low-fidelity exploration of dozens of concepts • Validate ideas faster through simulated user perspectives (e.g., walking through the product as different personas) • Apply your taste and judgment to identify the strongest directions from broad AI-assisted explorations, then invest your craft skills in fewer, higher-quality high-fidelity iterations • Work closely with product, marketing, engineering, and customer experience to inform and iterate on designs • Partner with engineering to ensure seamless design-to-development handoffs

• Own the full design process: from research and discovery through wireframes, prototypes, and polished UI • Design intuitive, accessible, and visually compelling experiences that translate complex financial problems into clear user flows • Evolve our design system to ensure consistency and scalability across the product • Use data, user research, and experimentation to continuously validate and improve designs • Apply AI to supercharge upfront research, competitive analysis, and rapid low-fidelity exploration of dozens of concepts • Validate ideas faster through simulated user perspectives (e.g., walking through the product as different personas) • Collaborate across teams with product, marketing, engineering, and customer experience to inform and iterate on designs

• Own product areas end-to-end, shaping both the problems we tackle and how we solve them • Often start from a blank slate, and iterate based on data • Make pragmatic, data-driven tradeoffs between speed, quality, user experience, and scalability • Develop and communicate product opinions backed by evidence • Help establish patterns and norms for product-oriented engineering

• Own backend systems and infrastructure end-to-end, from design through deployment and scaling • Build performant, reliable APIs and services that power our financial products • Design and implement scalable architectures on AWS using Node (TypeScript) • Make pragmatic tradeoffs between speed, reliability, scalability, and maintainability • Ship production code frequently while maintaining high quality standards • Help establish technical patterns and best practices for the engineering team • Interface effectively with product engineers and other stakeholders

• Build AI CX agents that process all incoming tickets • Review AI agent performance and real customer interactions to ensure automation handles more cases efficiently while maintaining high quality and customer satisfaction • Identify patterns across conversations and use them to improve agents, workflows, and self-serve experiences • Build, refine, and actively manage AI-driven support logic • Proactively expand automation into new areas to reduce manual work and increase system coverage • Support customers on complex, sensitive, or edge-case issues that require manual investigation • Handle escalations and high-stakes scenarios with care and ownership • Follow issues through until there is a real resolution

• Own and evolve Kovo’s lifecycle marketing strategy across email, push notifications, and in-app messaging. • Audit and optimize existing lifecycle programs, identifying opportunities to improve activation, engagement, retention, and long-term customer value. • Design and scale event-driven lifecycle programs to support personalized, behavioral-triggered messaging. • Build and maintain a modular email design system/library, leveraging AI tools to increase speed and quality. • Partner with Product and Data to ensure lifecycle messaging is tightly integrated with product events and user behavior. • Own conversion rate optimization: define the experimentation framework, prioritize and sequence tests across lifecycle messaging and web conversion flows, and document learnings. • Explore and implement AI-powered workflows and proactive messaging agents to improve personalization, cross-sell, and product discovery. We believe AI fundamentally changes what a small lifecycle team can do - you'll have the mandate and resources to prove that out. • Define lifecycle KPIs and continuously optimize for measurable performance improvements.

• Build AI CX agents that process all incoming tickets • Review AI agent performance and real customer interactions to ensure automation handles more cases efficiently while maintaining high quality and customer satisfaction • Identify patterns across conversations and use them to improve agents, workflows, and self-serve experiences • Build, refine, and actively manage AI-driven support logic • Proactively expand automation into new areas to reduce manual work and increase system coverage • Support customers on complex, sensitive, or edge-case issues that require manual investigation • Handle escalations and high-stakes scenarios with care and ownership • Follow issues through until there is a real resolution