Full Stack Engineer

About FinArb

FinArb is a data-driven analytics and AI consulting firm that builds automated, scalable solutions for complex business problems. We ship production applications and AI-powered products for clients across banking, finance, risk, healthcare, pharma, and education. Our engineering philosophy favors modern cloud-native platforms, strong fundamentals, and a ‘buy first, build the defensible core‘ approach — we pick the right tool for each problem rather than forcing stack.

About the Role

You‘ll own features end to end — from data model and API to UI and deployment — across our web applications and AI products. This is a hands-on senior role: you‘ll architect and build full-stack systems, integrate LLM-driven capabilities (agents, retrieval, tool/function calling), and take responsibility for quality, performance, and shipping. You‘ll work in both TypeScript/Node and Python ecosystems depending on the engagement, deploy to AWS or Azure, and collaborate closely with data scientists, designers, and client stakeholders.

Responsibilities

• Design, build, and ship full-stack features across frontend, backend, and data layers.
• Build and consume well-designed REST/GraphQL APIs and services; model the data behind them.
• Develop modern, responsive UIs and the server-side logic that powers them.
• Integrate LLM/AI capabilities into applications — agents, retrieval-augmented generation, tool/function calling, and orchestration.
• Deploy, monitor, and maintain applications on cloud infrastructure (AWS or Azure).
• Own code quality through reviews, testing, and sound engineering practices.
• Collaborate with data scientists, analysts, designers, and stakeholders to translate requirements into working software.
• Contribute to architectural decisions and continuous improvement of the team‘s standards and tooling.

Basic Qualifications

• Bachelor‘s or Master‘s in Computer Science, Engineering, or a related field — or equivalent practical experience.
• 3–5 years of hands-on full-stack development experience.
• Strong proficiency in JavaScript/TypeScript and at least modern frontend framework (React, Next.js, or similar).
• Solid backend experience in Node.js and/or Python, building and integrating APIs and services.
• Strong SQL and relational database skills; comfortable with schema design and data modeling.
• Experience deploying and running applications on a major cloud platform (AWS or Azure).
• Familiarity with Git, CI/CD, and modern software engineering best practices.
• Strong problem-solving and debugging skills; effective communicator in a cross-functional team.

Preferred Qualifications

• Hands-on experience building AI/LLM-powered applications — frameworks such as LangGraph or LangChain, the MCP (Model Context Protocol), or agent/RAG architectures.
• Infrastructure-as-code (CDK, SST, Pulumi, Bicep, or Terraform) and container/serverless deployment (ECS, Lambda, Container Apps).
• Experience with serverless and edge frameworks (e.g. SST, OpenNext) and full-stack platforms like Next.js in production.
• Exposure to NoSQL, vector stores, or other AI-adjacent data infrastructure.
• Familiarity with Go or Rust.
• BI/visualization or data-product experience.
• Awareness of data governance and handling of sensitive data (PII/PHI), and compliance frameworks (SOC 2, HITRUST) — relevant for our healthcare and finance clients

• Exam Link: https://www.autoproctor.co/tests/bfIxNc90WC/instructions/

• Bachelor's or Master's in Computer Science, Engineering, or related field — or equivalent practical experience
• 3–5 years of hands-on full-stack development experience
• Strong proficiency in JavaScript/TypeScript and at least modern frontend framework (React, Next.js, or similar)
• Solid backend experience in Node.js and/or Python, building and integrating APIs and services
• Strong SQL and relational database skills; comfortable with schema design and data modeling
• Experience deploying and running applications on a major cloud platform (AWS or Azure)
• Familiarity with Git, CI/CD, and modern software engineering best practices
• Strong problem-solving and debugging skills; effective communicator in a cross-functional team
• Hands-on experience building AI/LLM-powered applications — LangGraph, LangChain, MCP, or agent/RAG architectures
• Infrastructure-as-code (CDK, SST, Pulumi, Bicep, or Terraform) and container/serverless deployment (ECS, Lambda, Container Apps)
• Experience with serverless and edge frameworks (e.g. SST, OpenNext) and full-stack platforms like Next.js in production
• Exposure to NoSQL, vector stores, or other AI-adjacent data infrastructure
• Familiarity with Go or Rust
• BI/visualization or data-product experience
• Awareness of data governance, handling of sensitive data (PII/PHI), and compliance frameworks (SOC 2, HITRUST)