1 day ago
Toronto, CanadaStaff+
Responsibilities
- Build and own platform capabilities for AI-agent orchestration, retrieval, model routing, tool integration, and reliability.
- Design retrieval systems for large-scale legal document collections.
- Develop shared services for prompt management, caching, rate limiting, cost attribution, APIs, and data contracts.
- Create evaluation frameworks and observability, tracing, replay, monitoring, and quality-gate capabilities.
- Optimize model selection, inference strategies, latency, throughput, scalability, and cost across interactive and batch workloads.
- Build reliable systems with monitoring, alerting, incident response, governance, auditability, and human-in-the-loop controls.
- Ensure compliance with security, privacy, and data-residency requirements for legal and regulated workflows.
- Set technical direction through design documents and architecture decision records, and mentor engineers through reviews, pairing, and collaboration.
- Partner with Product Management, legal domain experts, and Review Operations to turn ambiguous problems into shippable scope.
Requirements
- Bachelor’s or master’s degree in computer science or a related technical field, or equivalent practical experience.
- At least 7 years building production software and owning systems end to end.
- Production AI/LLM systems experience, including retrieval-augmented generation and agentic workflows.
- Strong Python skills and comfort working in a TypeScript codebase.
- Experience with distributed systems, asynchronous and event-driven architectures, and large batch data processing.
- Demonstrated production reliability ownership, including instrumentation, on-call, incident response, and data-driven performance work.
- Clear written communication and ability to explain technical decisions and trade-offs to technical and non-technical audiences.
- Preferred experience with LangGraph, LangChain, MCP, Langfuse, OpenTelemetry, vector databases, search infrastructure, information retrieval, hallucination detection, grounding verification, benchmarking, model fine-tuning, quantization, inference optimization, React, legal technology, eDiscovery, compliance, investigations, document review, multi-tenant SaaS, and PostgreSQL.
Benefits
- Annual discretionary bonus eligibility is noted in addition to the base compensation range.
- Enterprise-wide learning and mobility opportunities are offered.
- The company describes flexibility and respect for life beyond work as part of its workplace culture.
- Applicants must be authorized to work in Canada and provide proof of right to work if required.
Tech Stack
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