Lead/Principal Full-Stack Engineer — Build AI-Driven Systems

Sahaj Software; Austin (TX); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Unlimited leave

Transparent salaries

Job summary

Sahaj Software is seeking a Lead or Principal Engineer in Austin to stay close to code, push the envelope, and build data-heavy, distributed software where AI becomes part of the system. You will mentor others, ship production-grade systems, and own design decisions in a fast-moving team.

You’ll tackle ambitious problems—designing scalable backends, redesigning data schemas, and delivering high-impact features across the stack—while maintaining focus on code quality and maintainability.

Qualifications

• 10+ years raising the bar for backend or full-stack engineering.
• Experience shipping production systems with real-world scale.
• Ability to mentor and raise code quality through pairing and feedback.
• Comfort working across multiple languages and AI-enabled systems.

Responsibilities

• Design and build systems with real-world complexity.
• Write production code frequently, not just reviews.
• Build services that interface with modern AI stacks (APIs, embeddings, vector databases).
• Ship robust, production-level AI-powered systems.
• Work across languages when needed, beyond your comfort zone.
• Break down messy problems into clean, maintainable systems.
• Push back on bad ideas, including ours.

Skills

10+ years backend/full-stack impact

Mentoring via pairing

Deep system thinking

Ability to work across languages

Tools

TypeScript

Java

Scala

Kotlin

Go

Elixir

Python

.NET

Node.js

Rust

Job description

Sahaj Software is seeking a Lead or Principal Engineer in Austin to stay close to code, push the envelope, and build data-heavy, distributed software where AI becomes part of the system. You will mentor others, ship production-grade systems, and own design decisions in a fast-moving team.

You’ll tackle ambitious problems—designing scalable backends, redesigning data schemas, and delivering high-impact features across the stack—while maintaining focus on code quality and maintainability.