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Salary: USD 240,000 - 300,000 / annual
Traba is building an AI operating system for the industrial supply chain, automating workflows across warehouses, manufacturers, logistics providers, and staffing operations. The company started as a fast-growing temporary staffing platform and has expanded into a suite of AI agents that help industrial businesses automate manual workflows, derive data insights, and improve decision intelligence.
As Staff Software Engineer (Applied AI), you will architect and build Traba's product on top of frontier AI models and agents. You'll own the core backend services and platform that powers the staffing marketplace—automating the pipeline that sources, vets, matches, and places workers on millions of shifts. This is fundamentally a platform-engineering role where you'll move fluidly across infrastructure, matching algorithms, data systems, and scaling challenges as priorities shift.
You'll join the founding team, partner directly with the CTO on architectural decisions, shape the roadmap, and build the foundational systems that will scale over several years. You'll set the standard for how the team applies agents across the full stack and integrates frontier models into production.
Key responsibilities include: architecting core systems (real-time matching, autonomous vetting pipelines powered by ML/agents); owning platform architecture with a 1-2 year forward view; driving backend performance, reliability, and scale; and establishing best practices for AI-assisted development and agent integration.
You bring 7+ years of full-stack experience with TypeScript/Node.js or Python, PostgreSQL, and messaging systems (Kafka/RabbitMQ). You have a proven track record shipping and leading projects at scale with high velocity. Experience building or integrating AI/LLM systems in production is valuable; what matters most is the judgment to lead the team into new territory. You're comfortable with ambiguity in an early-stage environment and move easily across API design, data modeling, query optimization, and distributed systems.
