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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Fullstack Engineer, Growth - **Company:** WASTED TALENT POOL SERVICE, LLC - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $35,360.0 - **Contract:** Permanent contract - **Skills:** Testing (Software), Artificial Intelligence, Amazon Web Services, Confluence, Continuous Integration, PostgreSQL, Node.Js, Online Transaction Processing, Standard Sql, SQL Databases, TypeScript, Datadog, Okta, Snowflake, Grafana, Apache Spark, Backend, Agentic-AI, Event Driven Architecture, Build Management, Kubernetes, Apache Kafka, Graphql, Api Gateway, OpenSearch, Jenkins - **Published:** October 12, 2026 - **Apply:** https://www.builtincolorado.com/auth/login?destination=/job/senior-fullstack-engineer-growth/11609909 ## About the Role Years of Experience: 4 - 7 years * Strong backend product engineering experience, most likely in TypeScript/Node.js, with real ownership of funnel-critical, production services * Hands-on experience with event-driven architectures and workflow orchestration - workflow engines or event pipelines that evaluate state continuously and trigger actions automatically * Genuine experimentation rigor: you've designed experiments properly, you understand guardrail metrics, and you know when a result is real versus noise * Strong SQL and warehouse fluency (Snowflake or similar), and the confidence to do your own cohort and funnel analysis rather than waiting on a data team * Comfort using AI agents to build and test software and to draft and sanity-check analytical work, paired with the judgement to catch the subtle errors a reasonable-looking AI output can hide * High tolerance for ambiguity - you're energised by problems that don't have an established playbook, not just ones with a clear spec * Practical fluency evaluating AI-generated output for fitness before it ships, whether that's copy, messaging, or a suggested root cause Nice to have * Direct experience integrating with identity verification, KYB/KYC, or fraud and risk providers * Fintech-adjacent experience handling credit, payment, or other sensitive financial data responsibly * Experience in a high-growth marketplace or fintech environment with similar account lifecycle complexity * Familiarity with workflow/orchestration tooling such as Temporal, AWS Step Functions, or event-streaming platforms like Kafka ## Description We're hiring a Senior Engineer for the Growth Pod to own both the backend systems and the front-end experiences that turn a new sign-up into an active, paying customer - the services and screens that decide whether a business converts or falls out of the funnel. The problems worth solving here span Sign-up/Onboarding, Discovery, and Checkout: you'll build the event-driven, always-on backend systems that track thousands of accounts through activation, slipping, winback, lapsed, and churned states in real time, and the seamless front-end moments that educate customers, represent the Nivoda brand, and move them toward a purchase. This isn't a role where you ship a spec and move on: you'll be expected to dig into the data yourself to work out what's actually going wrong when conversion isn't where it should be. You'll also work with identity verification and risk providers and with sensitive credit and payment data, so judgement and rigor matter here as much as raw engineering skill. Tech Stack * Search: OpenSearch fed via CDC from PostgreSQL plus Spark/EMR/Glue ingestion jobs. * Core DB / warehouse: PostgreSQL (OLTP) * Snowflake (dbt-modeled, medallion raw/curated/presentation layers) * Backend: TypeScript/Node.js, GraphQL API gateway, Nx monorepo + PNPM * Auth: Keycloak ยท SSO: Okta * CI/CD: Jenkins ("Nivoda Build") + GitOps for deploys * Cloud: AWS (EMR, Glue, DMS, Kubernetes-based deploys) * Observability: Grafana for logs/traces - I'd flagged Datadog as a guess earlier based on the Frontier agent skill descriptions; the real Confluence docs point to Grafana instead, so I've dropped Datadog from both JDs. What would you be doing? Core Funnel & Lifecycle Systems * Own and evolve the backend services behind onboarding, verification, activation, and the broader sign-up-to-purchase funnel, most likely in TypeScript/Node.js given our stack * Design and build event-driven, workflow-orchestrated systems that evaluate account state continuously - activation, slipping, winback, lapsed, churned - and trigger the right action automatically, rather than relying on batch scripts Identity, Risk & Trust * Integrate with third-party identity verification, KYB/KYC, and fraud/risk providers, and make sure those integrations are resilient, well-monitored, and fail safely * Handle credit and payment data responsibly as part of personalization and reactivation logic, with full awareness of what's at stake if that logic is subtly wrong Experimentation & Analysis * Design and run experiments properly - including defining guardrail metrics and knowing when a result is real versus noise - for things like referral incentives, reactivation offers, and onboarding changes * Write your own SQL and work directly in the warehouse (Snowflake or similar) to run cohort analysis, diagnose time-to-activation and time-to-churn, and get to the bottom of funnel problems without waiting on a data team * Take on problems that don't have an established playbook - like a credit utilization gap or a signup-to-purchase conversion decline - and help define the problem, not just solve a given brief Building with AI * Use AI agents to accelerate building and testing funnel and lifecycle services, with extra care reviewing anything that touches credit, payment, or verification logic * Use AI to help draft and sanity-check your own analytical queries, while owning full responsibility for verifying results before they inform a real decision * Evaluate AI-generated output - personalized messaging, reactivation copy, churn-cause suggestions - critically, rather than shipping whatever the model produces uncritically