This role involves building and scaling systems that reconcile latency, correctness, and observability across distributed pipelines, focusing on the safe deployment of AI technologies.

In Short

Architect scalable, low-latency services for real-time and batch evaluations.
Design and build core evaluation engines to detect violations across LLM inputs and outputs.
Implement runtime intervention layers for appropriate enforcement actions.
Create reusable frameworks for evaluators and intervention policies.
Configure a vector database pipeline for RAG-like use cases.
Build for scale and mitigate blocking gRPC threads.

Requirements

5+ years of Backend software engineering experience.
Strong coding proficiency in Python and/or Go.
Deep experience with streaming data pipelines.
Proven track record in scaling high-QPS, low-latency services.
Familiarity with vector databases.
Strong grasp of cloud-native infrastructure.
Exposure to observability patterns.
Ability to design trade-offs around build vs buy vs OSS.

Benefits

Opportunity to work on impactful AI safety projects.
Autonomy in a small, focused team.
Collaborative work environment valuing clear communication.
Engagement with customers to shape product development.

ThirdLaw

ThirdLaw is a pioneering company focused on creating the control layer for AI in enterprise environments. As organizations increasingly adopt large language models (LLMs) and AI agents, they encounter new challenges related to safety, compliance, and operational risks that traditional observability tools cannot address. ThirdLaw aims to empower IT and Security teams to assess and manage these risks in real-time, ensuring that AI systems operate safely and effectively. Backed by leading venture firms and collaborating with innovative enterprise partners, ThirdLaw is dedicated to building infrastructure that monitors, evaluates, and controls AI behavior in real-world applications, particularly at runtime. The company values autonomy, proactive problem-solving, and clear communication, fostering a small, focused team environment where impactful contributions are prioritized.

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