About the Company
ThirdLaw is building the control layer for AI in the enterprise. As companies rush to adopt LLMs and AI agents, they face new safety, compliance, and operational risks that traditional observability tools were never designed to detect. Metrics like latency or cost don’t capture when a model makes a bad decision, leaks sensitive data, or behaves unpredictably.
We help IT and Security teams answer the foundational question: "Is this OK?"—and take real-time action when it’s not.
Backed by top-tier venture firms and trusted by forward-looking enterprise design partners, we’re building the infrastructure to monitor, evaluate, and control AI behavior in real-world environments—at runtime, where it matters. If you're excited to build systems that help AI work as intended—and stop it when it doesn’t—we’d love to meet you.
About the Role
You won’t just be piping logs or tuning models—you’ll architect systems that reconcile latency, correctness, and observability across distributed pipelines. You’ll be designing the nervous system of a new class of software—where AI Agents reason, act, and fail in unpredictable ways. If you're excited by AI and want to shape its safe deployment—not just watch from the sidelines—this is your opportunity.
What You’ll Do
Architect and evolve core backend systems—event ingestion, real-time risk evaluation, semantic search, and investigation-grade querying.
Design and optimize streaming data pipelines using Kafka, Redpanda, or similar technologies to support high-throughput, low-latency processing of LLM interactions.
Define and refine data models and schemas across structured (Postgres), analytical (ClickHouse), unstructured (S3), and vector (Qdrant) storage layers.
Identify architectural weaknesses and performance bottlenecks across ingest, indexing, and query layers; lead improvements to support scalability, correctness, and observability.
Implement data ingestion and transformation frameworks that support policy evaluation, semantic analysis, and dynamic response.
Optimize query performance, storage efficiency, and retrieval accuracy to support deep investigation and real-time enforcement.
Build and maintain backend APIs, monitoring infrastructure, and policy enforcement workflows that underpin the ThirdLaw platform.
Who We are Looking For
You’ll be one of the first backend hires, helping define not just what we build, but how we build it.
Required
10+ years of backend or data engineering experience, ideally with a focus on distributed systems or streaming architectures.
Strong in Golang and/or Python; experienced with gRPC, REST, and working in Unix/Linux environments.
You’ve been the architect behind at least one complex distributed system—ideally involving real-time data, search, or observability—and can explain your design decisions clearly.
Familiarity with schema evolution, ORMs, and data mapping strategies in evolving analytics systems.
Comfort working with Kubernetes and cloud-native services in AWS/GCP/Azure.
Ability to debug deeply, reason about performance tradeoffs, and own systems end to end.
Nice-to-Have
Experience with semantic search, vector embeddings, AI agent infrastructure (e.g. LangChain, CrewAI, Autogen, etc.) and integrating LLM telemetry or foundation model outputs into observability pipelines.
Familiarity with OpenTelemetry, event trace modeling, Model Context Protocol (MCP), or real-time AI evaluation architectures.
Based in or willing to spend time in the San Francisco Bay Area for in-person collaboration.
Join us as we pursue our mission to unlock the boundless possibilities of generative AI by ensuring AI trust and safety. We're looking for people who bring thoughtful ideas and aren't afraid to challenge the norm.
Our team is small and focused, valuing autonomy and real impact over titles and management. We need strong technical skills, a proactive mindset, and clear written communication, as much of our work is asynchronous. If you're organized, take initiative, and want to work closely with customers to shape our products, you'll fit in well here.