Full Stack Engineer

Role overview

Product delivery

• Design, build, and own features across React and Next.js interfaces, Node.js and NestJS services, APIs, and data models.
• Build and maintain RESTful APIs and integrations with card issuing, banking, ERP, accounting, and other third-party providers.
• Translate business requirements into technical designs and explain trade-offs to product, finance, and operations stakeholders.
• Troubleshoot production issues, participate in on-call and incident response, and improve development processes and CI/CD.

Security and compliance

• Ensure shipped work meets security, privacy, and compliance obligations around authentication, authorization, payments, cardholder data, and personal information.
• Write clean, documented, tested code and keep changes small enough to be reviewed properly.

AI-assisted delivery

• Use agentic coding tools such as Claude Code, Cursor, GitHub Copilot, or equivalent to decompose work and direct implementation.
• Review, test, and harden AI-generated code before production and remain accountable for every line in submitted changes.
• Maintain repository instructions, reusable prompts, MCP connections, and current architecture documentation.
• Share effective workflows and help establish standards for safe and effective AI-assisted development.

AI product development

• Build AI-powered product capabilities using providers such as OpenAI, Anthropic, or AWS Bedrock.
• Implement retrieval, tool calling, evaluation harnesses, cost and latency budgets, and safeguards against prompt injection and data leakage.

Core engineering qualifications

• Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience.
• At least 5 years of experience building and running production web applications as a full-stack engineer.
• Production experience with React, Next.js, TypeScript, JavaScript, Node.js, NestJS, and TypeORM.
• Experience with PostgreSQL and at least one NoSQL store such as MongoDB, DynamoDB, or Cassandra.
• Experience with AWS, containerized services, CI/CD, automated testing, and production observability.
• Experience with RESTful APIs, microservices architecture, and API gateways.
• Strong software design and secure coding skills for systems handling financial and personal data.

AI engineering qualifications

• Demonstrable day-to-day production use of at least one agentic coding tool is required.
• Ability to provide agents with specifications, constraints, examples, and repository context is required.
• Test-first workflows, reviewable commits, checkpointing, rollback, and verification of generated code are required.
• Candidates must understand generated-code security risks and data-handling boundaries for third-party AI models.

Preferred experience

• Production experience integrating LLM APIs, including streaming, retries, timeouts, token and cost control, caching, and graceful degradation, is preferred.
• Experience with retrieval-augmented generation, vector search, structured outputs, and tool or function calling is preferred.
• Experience evaluating LLM features and knowledge of OWASP risks for LLM applications are preferred.
• Experience in fintech, payments, or another regulated domain is preferred.

Working competencies