Lead Software Engineer AI (Staff Engineer)
On-siteToronto, Ontario, Canada or Frisco, Texas, United States
Job Summary
Lead multi-quarter initiatives spanning AI, product, and infrastructure to design end-to-end backend systems for Audit Suite, including orchestration layers, low-latency retrieval, and unified knowledge bases. Own architecture for C#/.NET and Python services that integrate heterogeneous stacks, manage millions of documents, and enforce safety guardrails for third-party LLMs. Mentor senior engineers while shaping team patterns for MCP servers, agent design, and experimentation practices. Collaborate directly with product leadership and customers to deliver reliable, auditable workflows for accountants in high-throughput, time-sensitive environments.
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, a related field, or equivalent experience
- Overall 10+ years cumulative experience
- 2 years in a lead role
- minimum 5+ years full-stack development, building scalable cloud-based applications, web services, APIs and AI-driven products
- C#, .NET expertise
- experience with production systems using frameworks like ASP.NET Core (or similar)
- relational databases (SQLServer, PostgreSQL or equivalent)
- a major cloud provider (AWS preferred, Azure)
- Experience architecting and implementing accessible front-end solutions
- JavaScript
- Typescript
- HTML
- CSS
- experience with modern JavaScript frameworks, e.g., Angular, React, etc.
- Strong background in distributed systems: data modeling, API contracts, observability, resilience patterns, and performance tuning under load
- Proven track record leading large, complex projects end‐to‐end: architecture, execution, rollout, and long‐term operation
- Excellent communication skills
- the ability to partner with product, design, and ML teams in a fast‐moving environment
- Demonstrated interest in AI systems and new engineering paradigms: LLMs, agents, retrieval, or similar
Desired Qualifications
- Experience designing and implementing CI/CD pipelines (i.e., GitHub Actions)
- Hands‐on experience integrating LLM APIs (e.g., OpenAI, Anthropic) into production applications, including prompt/response management, cost controls, and safety considerations
- Experience with AI‐adjacent infrastructure: vector databases, embeddings, semantic search, or custom retrieval pipelines
- Opinions and experience around automated testing, reliability, and release practices for systems with non‐deterministic model behavior
- Prior experience in domains where correctness, auditability, and compliance matter (fintech, tax, audit, legal, or similar), or strong interest in applying AI in those contexts
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