Skeletons, lasers, monster trucks — the Torq brand grabs attention like nothing else in cybersecurity. And we’re growing like crazy, with $70M in Series C funding, 200% employee growth, and 300% revenue growth in 2024. Fueling Torq’s growth are our game changing agentic AI security solutions, backed by a team and culture that makes Torq one of Forbes’ Best Startup Employers in America, and a Business Insider ‘startup to bet your career on’.

Life at Torq is all gas, no brakes. We’re a team of relentless, collaborative go-getters pushing the boundaries of what’s possible for security automation. Every role is an essential driver of Torq’s success as the AI-native autonomous SecOps platform of choice for security teams across the Fortune 500. Excited about our vision and ready to make an impact as we grow? We’d love to see what you can bring to the team.

We are looking for an experienced AI Backend Engineer to join our fast-growing company during an exciting stage of innovation. In this role, you'll design and develop Agent and LLM-based features, engineer and optimize context and high-quality prompts, implement agentic architectures in production and  evaluate and monitor applications effectively. If you're passionate about staying at the forefront of Large Language Model AI applications and collaborating with a team of experts, we’d love to hear from you!

What Will You Do?

• Take part in all development aspects, from design to production, of Agent and LLM-based features and applications.
• Take part in all the development and planning aspects of a backend application, understanding scale, performance, observability.
• Craft and optimize high-quality prompts to enhance application functionality and output quality.
• Develop datasets and benchmarks to evaluate and monitor LLM-based applications effectively.
• Stay up to date with state-of-the-art research in the field of Large Language Models and apply relevant advancements to improve our applications.
• Collaborate closely with other team members and contribute to a culture of innovation and continuous improvement.
• Mentor new team members and share your expertise to strengthen the team's collective knowledge.

What Should You Bring to the Table?

• Significant real-world experience (at least 5 years) of developing software for production backend systems (Go, Python, Typescript, Node etc).
• Proficiency in LLM application concepts and techniques such as Agentic Memory,  Retrieval-Augmented Generation (RAG), embeddings, Multiagent systems, and more.
• Hands-on experience with measuring AI systems - developing datasets, evaluation benchmarks, and performance monitoring systems for LLM applications.
• A solid understanding of state-of-the-art advancements in the field of Large Language Models .
• Ability to take initiative, scope work iteratively, and make meaningful design decisions to drive projects to completion.

Preferred Qualifications

• A strong focus on data and data quality, with the ability to optimize data flows for developing cutting-edge LLM-based applications.
• Familiarity with Langchain, LangGraph or other LLM-based frameworks
• The ideal candidate possesses a data science mindset combined with an engineer's agility and focus on swiftly bringing solutions into production.

As an equal opportunity employer, we are committed to a team defined and empowered by diversity. We consider qualified applicants without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.