Forward Deployed Engineer, Operations

Alternative Payments•New York, NY

1d•$200,000 - $250,000

About The Position

Alternative Payments is building the financial operating system for SMBs, consolidating the disconnected tech stack that holds service-based businesses back. Starting with MSPs, we've spent five years perfecting accounts receivable, and we're now expanding into accounts payable, AI-powered analytics, and beyond. We're at an inflection point: closing the loop on money movement and laying the foundation for a platform that will reshape how service businesses operate financially. We're growing fast, thinking big, and building a global team that wants to be part of something that lasts. We believe the best solutions come from diverse perspectives, deep collaboration, and a shared obsession with customer impact. If you're energized by real problems, real customers, and real impact, we want to hear from you! We're looking for a Forward Deployed Engineer who can take a real business problem, understand why it matters, and build the system that solves it. You'll own initiatives end to end, partner closely with operations, data, and product, and explore net-new product POCs and build internal tooling, automations and AI agents / agentic workflows that help the whole company move faster. This is an internal-facing role. Your customers are our own Ops, Product, Customer Success and Sales teams. Think of it as playing forward-deployed engineer for Alternative Payments itself: embedded with the teams that need you, understanding their real problems, and building the systems that solve them. Examples of what’s you’ll own: Internal AI data infrastructure that consolidates what we know about our business and makes it usable across teams. Put AI at the center of how you work. We're an AI-forward team and expect you to build with it by default, leveraging it in your daily workflows as well as for team enablement, not just basic usage. Building products we'd otherwise buy. We're replicating internal versions of Sales, CS, Marketing tools, built to fit exactly how we operate instead of bending our workflows to someone else's SaaS. The dashboards that run the business. Our Ops dashboard, Finance dashboard, and the Super Admin dashboard, plus the automations behind them. This means understanding why something matters to the business, not just what needs to be built. Own the work that starts as a prototype and has to become a real system: internal applications and automations, product integrations, features for new verticals, and agentic workflows hardened into deterministic ones. Net-new product POCs. Working directly with the Product Engineering team on early-stage ideas before they become full initiatives, bringing business context and translating it into technical decisions. Guardrails on AI-assisted development. Our BizOps team ships production code with AI assistance. You'll review that work (architecture, infrastructure decisions, PRs) to make sure it's safe, reliable, and doesn't quietly generate tech debt we have to unwind later. Build for reliability, not just speed. Design and build systems with real attention to reliability, performance, and maintainability. This is software that moves real money, so the bar is production-grade from day one. Plug into the engineering team through code review, architecture feedback, and shared standards, so what you ship is production-grade and you get sharper with every initiative. You'll sit within Engineering but work alongside our Business Operations and Product Engineering teams. You will support our non-technical subject matter experts in deploying product to our production codebase, building systems from scratch and refining our coding harnesses to make them more use-friendly for non-technical users. We run parallel initiatives in small, high-autonomy teams, and we expect the people who join us to step up, make decisions, and take accountability for outcomes, technical and otherwise.

Requirements

Deep architectural knowledge.
Platform/infrastructure fluency (understanding Kubernetes, cloud infrastructure, data pipelines).
Strong software engineering ability within a full-stack range.
Ability to ship production code independently and own real systems end to end.
Comfort moving between frontend and backend.
An AI-native operating bias; using multiple models, custom agents, and specialized contexts.
Proficiency in, or ability to quickly ramp on, TypeScript, Next.js, and Python for internal tooling.
Proficiency in, or ability to quickly ramp on, Go or Rust, Kubernetes, PostgreSQL, and AWS on the core platform.
Experience designing and evolving scalable systems, with a clear point of view on tradeoffs.
Demonstrated ability to take a project from end-to-end: technical execution, stakeholder communication, and delivery accountability.
Cross-functional instincts; comfortable moving between Operations, Product, and Data.
A bias toward business impact; desire to solve real operational problems and understand business operations.
Comfort operating in ambiguity, with the judgment to work autonomously, make decisions, and take accountability for outcomes.
Pragmatism and speed; knowing when to build fast and scrappy versus bulletproof.

Nice To Haves

Experience at a fintech or payments company, or working close to how money moves.
Experience contributing to billing, payments, or quote-to-cash systems.
Experience building internal tools, admin panels, or business-facing dashboards.
Familiarity with event-driven architectures (RabbitMQ or similar).
Background at a fast-scaling startup, or anywhere owning systems end-to-end close to the business.

Responsibilities

Own initiatives end to end, partnering closely with operations, data, and product.
Explore net-new product POCs and build internal tooling, automations, and AI agents/agentic workflows.
Build internal AI data infrastructure that consolidates business knowledge and makes it usable across teams.
Build internal versions of Sales, CS, and Marketing tools.
Develop dashboards that run the business, including Ops, Finance, and Super Admin dashboards, plus the automations behind them.
Take work from prototype to a real system: internal applications, automations, product integrations, features for new verticals, and agentic workflows.
Work with the Product Engineering team on early-stage ideas for net-new product POCs.
Review AI-assisted development work (architecture, infrastructure decisions, PRs) to ensure safety, reliability, and prevent tech debt.
Design and build systems with attention to reliability, performance, and maintainability.
Plug into the engineering team through code review, architecture feedback, and shared standards.
Support non-technical subject matter experts in deploying product to the production codebase.
Build systems from scratch and refine coding harnesses for non-technical users.