ThirdLaw AI Logo

ThirdLaw AI

Backend / Platform Engineer, AI Analytic Engines

Reposted 5 Days Ago
Remote
Hiring Remotely in USA
Senior level
Remote
Hiring Remotely in USA
Senior level
The role involves architecting scalable backend systems for real-time evaluations, integrating with streaming data, and building intervention layers for AI applications. You'll design frameworks and operationalize vector databases while ensuring low-latency service performance.
The summary above was generated by AI
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 build and scale 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 scalable, low-latency services for running evaluations in real-time and batch, integrating with streaming data pipelines and trace-based event models.

  • Design and build the core evaluation engine within ThirdLaw that applies heuristics, semantic models, and foundation model calls to detect violations across LLM inputs and outputs.

  • Build a runtime intervention layer to determine and execute appropriate enforcement actions—such as block, redact, notify, escalate—based on evaluation results and risk context.

  • Create reusable frameworks for pluggable evaluators and intervention policies, supporting no-code authoring and automated deployment pipelines.

  • Configure and operationalize a vector database pipeline for RAG-like use cases.

  • Build for scale. Mitigate blocking gRPC threads, implement micro-batching & streaming for LLM/embedding calls and add reliability controls such as queue-based back-pressure and graceful degradation paths.


Who We Are Looking For
Required
  • 5+ years of Backend software engineering experience, including designing and shipping production software services

  • Strong coding proficiency in Python and/or Go

  • Deep experience with streaming data pipelines (e.g. Kafka, Pulsar, Redis Streams) and batch processing systems

  • Proven track record scaling high-QPS, low-latency services (p95/p99 ownership a plus).

  • Familiarity with vector databases (e.g. FAISS, Weaviate, Qdrant, pgvector) and embedding-based matching

  • Strong grasp of cloud-native infrastructure: containers, Kubernetes, serverless functions, CI/CD pipelines

  • Exposure to structured observability patterns, including OpenTelemetry (or similar tracing standards)

  • Comfortable designing—then defending—trade-offs around build vs buy vs OSS.

Nice-to-Have
  • Experience with modern Python APIs & concurrency, e.g. gRPC, FastAPI, asyncio, multithreading/processes

  • Familiarity with ClickHouse, Apache Arrow, or fast analytical storage engines

  • Prior work on agent frameworks (e.g. LangChain, CrewAI, AutoGen) or LLM orchestration

  • Experience in trust & safety, compliance, or AI safety domains

  • Hands-on experience with secure enterprise integrations (authorization/authentication, webhooks, SIEM, IAM)

Why Apply?

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.

Finally, we pay market cash compensation and generally above-market equity. The compensation package for this role is benchmarked using Carta Total Compensation and reflects real-time market data for our company’s size, this role’s level, and your geographic location. We have well-designed and generous benefits.

https://www.thirdlaw.io/

Similar Jobs

An Hour Ago
Remote or Hybrid
160K-200K Annually
Senior level
160K-200K Annually
Senior level
Fintech • Payments • Software
Manage and mentor the Site Reliability Engineering team, driving reliability and performance in cloud infrastructure, while fostering collaboration across software engineering teams.
Top Skills: AWSChefCloudwatchDockerDocumentdbEc2EcsElasticsearchGitlabGoHoneycombJavaJenkinsKinesisKotlinLambdaLinuxMakeNode.jsPythonRdsRubyS3SentrySqsSumologicTerraform
An Hour Ago
Remote or Hybrid
MA, USA
115K-150K Annually
Senior level
115K-150K Annually
Senior level
Fintech • Payments • Software
The role involves automating marketing workflows using AI, building data pipelines, and improving marketing operations to drive revenue and efficiency.
Top Skills: AIClaude CodeCursorGumloopMakeN8N
An Hour Ago
Remote or Hybrid
United States
55-65 Hourly
Mid level
55-65 Hourly
Mid level
Fintech • Payments • Software
The Compensation Consultant will support Workday implementation focusing on compensation design, system configuration, and day-to-day compensation support for APAC regions, ensuring accurate operationalization of compensation programs.
Top Skills: ExcelGoogle SheetsWorkday

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account