Software Engineer - AI Systems

xbowcareers; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity package

Remote-first setup

Full-time contract

Job summary

xbowcareers is hiring a software engineer to design and build the software that orchestrates large language models for an autonomous security platform. The work blends research-driven AI development with production engineering, focusing on prompting strategies, evaluation infrastructure, and reliable end-to-end systems that surface vulnerabilities with high precision.

You will design prompt flows, orchestration layers, and production-grade TypeScript software; build experiments to measure

Qualifications

• Hands-on experience building software around LLMs.
• Experience with prompting, agentic orchestration, and integration with deterministic logic.
• Strong production engineering background for reliable systems.
• Ability to work in fast-paced, research-oriented environments.
• MSc or higher in CS/math/physics/ML (or equivalent).

Responsibilities

• Design prompt flows and orchestration layers to deliver accurate results.
• Architect production-grade AI-powered software in TypeScript.
• Build experiments and evaluation frameworks for large-scale performance.
• Collaborate with researchers and engineers to ship end-to-end features.
• Own projects from ideation through deployment and monitoring.
• Track LLM research advances to improve speed and capability.

Skills

LLMs

Prompting

Orchestration

Fault tolerance

TypeScript

Production systems

Education

MSc in Computer Science, Mathematics, Physics, or ML

Job description

Role overview

Design and build the software that orchestrates large language models for an autonomous security platform. The work blends research-driven AI development with production engineering, focused on prompting strategies, evaluation infrastructure, and reliable end-to-end systems that surface real vulnerabilities with high precision.

Responsibilities

• Design prompt flows and orchestration layers that coordinate LLMs with deterministic logic to deliver accurate, low-false-positive results.
• Architect production-grade, testable, and maintainable AI-powered software in TypeScript.
• Build experiments and evaluation frameworks that measure system performance at scale, and turn data into actionable conclusions.
• Collaborate with AI researchers, security experts, and frontend and backend engineers to ship cohesive end-to-end features.
• Own projects across the full lifecycle, from ideation and experimentation through deployment and production monitoring.
• Track advances in LLM research and integrate promising techniques to improve speed and capability.

Requirements

• Hands-on experience building software around LLMs, including prompting, agentic orchestration, fault tolerance, and integration with hard-coded logic.
• Strong software engineering background with a track record of architecting reliable, maintainable production systems.
• Proficiency in TypeScript, or demonstrated ability to ramp up quickly on a new language.
• Structured, self-directed problem-solving skills and comfort working with incomplete information.
• Ability to thrive in a fast-paced, agile environment with a research-lab mentality.
• MSc or higher in computer science, mathematics, physics, or machine learning (or equivalent experience).

Nice to have

• Experience in offensive security or applying LLMs to security problems.
• Open-source contributions, especially around LLM frameworks or applications.
• A PhD in machine learning, computer science, or a related field.
• Prior startup experience and comfort navigating ambiguity.

Benefits and work setup

• Competitive compensation plus a meaningful equity package.
• Opportunity to help shape the function and grow alongside the team.
• Remote-first setup, with regular team meetups and support for in-person collaboration.
• Full-time contract.
• Hiring process: introductory chat, engineering lead conversation, technical deep dive around a relevant case study, and a final meeting with the engineering lead.