Forward Deployed Engineer

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Execute comprehensive end-to-end full stack features on our platform, including backend APIs and services, as well as customer-facing dashboards and operator tools for the frontend.

• Design and configure each client's lending ecosystem within Fuse, encompassing loan types, underwriting parameters, debt adjustment regulations, task flows, adverse actions, and email/e-sign templates.

• Develop and sustain client-specific automations and workflows that manage the entire loan lifecycle, integrating with credit bureaus, KYC providers, banking infrastructure, and document services.

• Deploy AI-driven features into production, including LLM-based automations, classification and extraction pipelines, agentic workflows, and tool-utilizing agents (e.g., MCP-style tool integrations) that function on actual customer data.

• Take ownership of features from inception to completion: including scoping, implementation, testing, deployment, monitoring, and iterations based on production feedback.

• Produce clean, well-tested, and observable code while contributing to our collective standards regarding code quality, reliability, and security.

⛳️ Requirements

• A minimum of 3 years of professional experience as a software engineer, preferably in a full-stack capacity.

• Strong expertise in a contemporary backend stack (Node.js/TypeScript, Python, Go, or similar) along with experience in designing and utilizing REST/GraphQL APIs.

• Solid frontend expertise with React (Next.js is a plus), TypeScript, and modern state management; capable of delivering polished, responsive user interfaces.

• Proficient in working with relational databases (PostgreSQL), crafting complex queries, and conceptualizing data models for transactional systems.

• Experience in deploying services to cloud platforms (AWS, GCP, or similar), with a solid grasp of CI/CD, observability, and fundamental operational practices.

• Proficient in English, both written and spoken; able to collaborate asynchronously with a distributed team.

• Practical experience in integrating LLMs (OpenAI, Anthropic, or equivalent) into production systems, rather than just prototypes or notebooks.

• Comfortable with prompt engineering, structured outputs, tool/function invocation, evaluation, and establishing guardrails for AI-driven functionalities.

• Familiarity with at least one of the following: retrieval-augmented generation (RAG), agentic workflows, MCP servers/clients, vector search, or LLM observability.

• A pragmatic understanding of when to employ AI versus deterministic logic, factoring in cost, latency, reliability, and risk considerations in regulated environments such as lending.

• Regular use of AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) with a well-defined perspective on their advantages and disadvantages.

🏝️ Benefits

• Competitive compensation

• Full coverage of the AI tooling stack

• Remote-first culture promoting strong autonomy

• Significant impact on the financial infrastructure utilized by credit unions and lenders throughout the U.S.

• Direct influence on the product roadmap and the future of lending practices in the region.