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.
What you'll do
We are looking for a Senior Software Engineer to solve complex technical problems and build dependable backend and platform systems that enable our product to scale. You will own work from design through production, balance near-term delivery with long-term maintainability, and help teammates grow.
Design, implement, and operate scalable backend services, APIs, and platform capabilities.
Build robust systems and services in Go and Python.
Own technical design, delivery, reliability, security, and operational quality for your domains.
Work with Product, Design, Data, and other engineers to deliver customer value quickly and safely.
Improve engineering foundations, including test coverage, observability, CI/CD, performance, and developer experience.
Apply AI-assisted engineering tools responsibly while maintaining strong technical judgment.
Requirements
7+ years of professional software engineering experience, or equivalent experience delivering senior-level work.
Strong production experience in Go or Python, with the ability to work effectively in both.
Experience designing and operating production-grade APIs and distributed systems.
Strong foundations in data modeling, testing, debugging, security, performance, reliability, and production operations.
A record of independently driving complex work from an unclear problem to a dependable outcome, while communicating tradeoffs clearly and helping teammates succeed.
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
Strong production experience with both Go and Python.
Experience with cloud infrastructure, containers, Kubernetes, queues, and asynchronous workflows.
Experience with LLM integrations, agentic workflows, evaluation systems, retrieval pipelines, or AI observability.
Experience in B2B SaaS, developer tools, data products, or regulated environments.