About the Role:
We are seeking a Backend / Systems Engineer to help build a flexible, robust, and high-performance backend architecture that serves diverse use cases across customers and product lines. Your work will be critical in enabling our AI engineers, analysts, and data scientists to rapidly prototype, iterate, and deploy workflows, services and data pipelines that leverage large language models (LLMs).
This is a high-impact role that blends backend engineering with thoughtful system design to accelerate product development and real-world impact of AI Systems, in particular LLMs.
Design and build extensible backend systems that support flexible configurations for different customers and content types.
Develop infrastructure that interfaces cleanly with LLMs, enabling prompt engineering, context injection, and modular evaluation workflows.
Build tooling and platforms that enable fast iteration by AI engineers and analysts, including declarative pipelines, parameterized jobs, and reproducible experiments.
Prioritize ease of deployment, integration, and testing, both for internal teams and external partners.
Collaborate closely with product, data, and policy teams to translate nuanced safety needs into scalable, maintainable software systems.
5+ years of experience in backend systems or infrastructure engineering.
Strong software engineering skills in Python, Go, Java, or equivalent.
Experience designing scalable APIs, backend systems and data pipelines.
Familiarity with LLM-based systems (e.g., prompt management, context formatting, batch inference, prompt-tuning workflows).
Strong understanding of cloud-native infrastructure (e.g., AWS, Lambda, Kubernetes, CI/CD pipelines).
Passion for building systems that unlock velocity and experimentation for cross-functional teams.
Background in trust & safety, or content moderation.
Familiarity with Django, Snowflake, React, Step functions.
Experience with LLM-Ops and DevOps.
Work with renowned industry leaders in AI and online safety who have built and scaled Trust & Safety systems at companies like Google, YouTube, TikTok, and Reddit, helping shape how technology operates responsibly at global scale.
Build greenfield systems from the ground up, with real ownership over core architecture rather than maintaining legacy platforms. This is a rare opportunity to define foundational infrastructure at a pivotal moment in AI adoption.
Apply AI technology to real-world, high-impact use cases at meaningful scale, including work with blue-chip and government customers, where reliability, trust, and accountability truly matter.
Work in an environment that values engineering rigor, sound judgment, and psychological safety, with the ability to focus deeply on your craft without unnecessary bureaucracy.
We offer competitive compensation, including a base salary range of $150,000–$220,000 USD, along with equity, comprehensive benefits, and a hybrid in-office work environment. Compensation is determined based on experience, skills, and scope of impact.