Senior AI Platform Engineer

epiqsystems; Toronto; On-site; CAD 126,000 - 175,000; Full time

Job summary

Epiq is seeking a Senior AI Platform Engineer in Toronto to design and build the platform powering AI agents and accelerators at scale. You will own major components end to end, mentor across Toronto, US, and India teams, and set technical direction for high-impact workflows.

The role covers platform engineering, evaluation, performance, reliability, and governance. You will collaborate with product teams to deliver defensible outcomes and cost-efficient large-scale document processing.

Qualifications

• Bachelor's or master's in computer science or equivalent experience.
• 7+ years building production software with end-to-end ownership.
• Experience with production AI/LLM systems and retrieval-augmented workflows.
• Strong Python; comfortable with TypeScript codebases.
• Experience in distributed, asynchronous architectures and large batch data processing.
• Proven ownership of reliability: instrumentation, on-call, incident response and data-driven improvements.
• Clear written communication for engineers and non-engineers.

Responsibilities

• Build and own platform capabilities powering AI agents and accelerators.
• Design retrieval systems for large-scale legal document collections.
• Develop shared services: prompts, caching, rate limiting and cost attribution.
• Define stable APIs and data contracts for product teams.
• Create evaluation frameworks for accuracy, grounding and performance.
• Implement observability, tracing, and replay for rapid troubleshooting.
• Ensure latency, throughput and scalability for interactive and batch workloads.
• Lead design reviews, code reviews, and mentoring across teams without direct reports.

Skills

Python

TypeScript

Distributed systems

On-call / incident response

Technical communication

Education

Bachelor's or Master's in Computer Science

Tools

LangGraph

LangChain

MCP

OpenTelemetry

PostgreSQL

Job description

At Epiq , your work contributes to complex, global legal outcomes. You'll join a values-driven community where integrity guides decisions, relentless service sets the bar, and we thrive on big challenges together. We invest in your growth with enterprise-wide learning and mobility. We celebrate who you are, and we respect life beyond work with flexibility that's recognized externally. Enabled by modern platforms and AI, you'll do the most meaningful work of your career and see your impact at scale.

Job Description

Epiq supports some of the world's largest and most complex legal matters, where document collections range from thousands to millions of records. As a Senior AI Platform Engineer, you will design and build the platform our AI agents and accelerators run on, including orchestration, retrieval, evaluation, observability, and the inference path that keeps all of it fast and affordable at production scale.

This is a senior individual contributor role. You will write production code; own significant components end to end. You will set the technical direction that other engineers build on. You will also mentor engineers across our Toronto, US, and India teams through design reviews, code reviews, and pairing.

You will work across two product areas:

• AI Agents. Conversational systems that enable legal professionals to ask complex questions and receive evidence-based answers grounded in case data.
• AI Accelerators. AI-powered workflows that automate large-scale document review tasks including summarization, translation, transcription, language detection, and OCR.

Together, these solutions help legal teams reach defensible outcomes faster while reducing review costs and improving quality.

What You’ll Do

Platform Engineering

• Build and own the platform capabilities that power AI agents, including orchestration, retrieval, model routing, tool integration, and reliability.
• Design retrieval systems across large-scale legal document collections.
• Develop shared platform services including prompt management, caching, rate limiting, and cost attribution.
• Define stable APIs and data contracts for product teams.

Evaluation & Quality

• Develop evaluation frameworks that measure accuracy, grounding, citation quality, and overall system performance.
• Build observability, tracing, and replay capabilities that enable rapid troubleshooting and continuous improvement.
• Establish quality gates and monitoring to identify regressions before they reach production.

Performance, Scale & Cost

• Optimize latency, throughput, and scalability across both interactive and batch workloads.
• Drive decisions around model selection, inference strategies, caching, and routing while managing cost as a first-class engineering metric.

Reliability & Governance

• Build highly reliable systems through monitoring, alerting, incident response, and operational excellence practices.
• Implement governance, auditability, and human-in-the-loop controls required for legal and regulated workflows.
• Ensure compliance with security, privacy, and data residency requirements.

Technical Leadership Without Direct Reports

• Write the design docs and ADRs for consequential platform decisions, including the trade‑offs you rejected.
• Raise the engineering bar through code review, pairing, and mentoring. Grow other engineers' judgment, not just their output.
• Partner with Product Management, legal domain experts, and Review Operations to turn ambiguous problems into shippable scope.

Required Qualifications

• Bachelor's or master's degree in computer science or a related technical field, or equivalent practical experience.
• 7+ years building production software, with a track record of owning systems end to end.
• Experience building production AI/LLM systems, including retrieval-augmented generation and agentic workflows.
• Strong Python. Comfortable in a TypeScript codebase.
• Experience with distributed systems, asynchronous and event-driven architectures, and large batch data processing.
• Demonstrated ownership of production reliability: instrumentation, on-call, incident response, and performance work driven by data rather than intuition.
• Clear written communication. You can explain a design decision and its trade-offs to engineers and to non-engineers.

Preferred Qualifications

• Orchestration frameworks such as LangGraph, LangChain, MCP, etc.
• LLM observability and evaluation tooling such as Langfuse, OpenTelemetry, etc tracing.
• Vector databases, search infrastructure, and information retrieval fundamentals.
• Hallucination detection, grounding verification, and benchmarking methodology.
• Model fine-tuning, quantization, or inference optimization.
• React and modern frontend work for internal evaluation and debugging tools.
• Legal technology, eDiscovery, compliance, investigations, or document review.
• Multi-tenant SaaS platforms with strict data isolation requirements.
• Experience with PostgreSQL.

The Compensation range for this role is $126,000 CAD up to $175,000 CAD ann.