Senior Full-Stack Engineer

About Factify

Factify is building the truth infrastructure layer for regulated AI. Regulated enterprises are moving from AI experimentation to production deployment, but the infrastructure for trust, governance, auditability, and deterministic AI work is still being defined. Our opportunity is to help shape that category before it hardens.

The role

We are looking for a Senior Full-Stack Engineer to build reliable, high-impact product experiences from browser to backend. You will own meaningful product areas, turn ambiguous customer problems into pragmatic technical solutions, and help set a high bar for quality, speed, and engineering judgment.

What you’ll do

Design, build, test, deploy, and operate end-to-end product capabilities.
Build polished frontend experiences with React and TypeScript.
Develop scalable backend services and APIs with Node.js and TypeScript.
Partner closely with Product and Design to shape solutions before implementation.
Make sound architecture decisions across application boundaries, APIs, data models, security, performance, and observability.
Use AI-assisted engineering tools thoughtfully to improve development speed and quality, while rigorously validating their output.
Build AI-enabled or agentic product capabilities where they create clear customer value.
Raise the engineering bar through code reviews, pairing, documentation, and mentorship.

Requirements:

7+ years of professional software engineering experience, or equivalent experience delivering senior-level work, including substantial full-stack ownership.
Strong production experience with React and TypeScript across frontend and backend development.
Strong experience with Node.js or another production backend stack, including API design and operation.
Deep understanding of web architecture, testing, security, performance, and production operations.
A record of independently delivering customer-facing products, communicating tradeoffs clearly, and following work through production.
Hands-on experience shipping AI-enabled or agentic capabilities to production with a framework such as LangGraph, CrewAI, or an equivalent, including disciplined validation of outputs.

Nice to have

Experience with Go.
Experience designing microservices, event-driven systems, or cloud-native applications.
Experience with LLM integrations, retrieval, evaluation, or AI workflow observability.
Experience with Docker, Kubernetes, CI/CD, and modern observability tooling.