26 days ago
Toronto, CanadaSenior
Responsibilities
- Design and build core agent platform capabilities, including orchestration patterns, tool execution layers, memory and context management, and guardrails.
- Develop reusable agent skills, standardized tool ecosystems, permissioning, policy enforcement, and human-in-the-loop execution controls.
- Design and implement RAG services with hybrid retrieval, reranking, embeddings, citation behavior, and quality evaluation metrics.
- Build automated evaluation and regression pipelines and establish tracing, metrics, alerting, latency, throughput, and cost optimization.
- Prototype and productionize GraphRAG, knowledge graphs, MCP integrations, and emerging AI approaches.
- Evaluate LangChain, LangGraph, AutoGen, LlamaIndex, and related AI frameworks and guide platform decisions.
- Diagnose complex AI system issues and lead system design, prototyping, benchmarking, and production-readiness practices.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, or a related field, or equivalent experience; an advanced degree is preferred.
- 5+ years of software engineering experience, including building and deploying production-grade LLM, agent, or RAG systems.
- Proven experience shipping and supporting AI-powered features in production.
- Strong Python skills, including API design, testing, error handling, and environment management.
- Working proficiency in C# or C++.
- Deep understanding of RAG system design and evaluation methodologies.
- Experience building evaluation frameworks with test sets, metrics, and regression pipelines.
- Understanding of LLM security risks, including prompt injection, data leakage, and agent misuse.
- Preferred experience with graph databases, knowledge graphs, GraphRAG, human-in-the-loop systems, execution controls, and agent frameworks.
- Ability and willingness to commute to the Toronto, Ontario office on a hybrid schedule once per week.
Benefits
- Estimated base salary is CAD $130,000-$165,000 plus bonus.
- Benefits include RRSP and medical/dental coverage.
- Hybrid work in the Toronto, Ontario office is required once per week.
- The role includes standard workplace accommodation support and an individual background review process.
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