Senior AI Engineer
Guidepoint7 hours ago
Toronto, CanadaSenior
Responsibilities
- Design and ship multi-agent workflows involving task planning, tool use, delegation, handoffs, and result synthesis.
- Implement permissions, domain rules, workflow boundaries, safe tool use, failure handling, and human review mechanisms.
- Build reliable multi-turn orchestration with explicit state, memory and context strategies, timeouts, retries, and partial-failure recovery.
- Develop and maintain Python services and APIs connecting agents to products, internal data, and third-party providers.
- Build retrieval and search pipelines that produce structured, traceable answers grounded in trusted knowledge assets.
- Define and maintain evaluations for task success, factual accuracy, groundedness, completeness, policy adherence, latency, and cost.
- Deploy and operate AI services using containers, Kubernetes, Azure, and Databricks.
- Select models and tools, engineer context, define structured outputs, and manage quality, latency, reliability, and cost tradeoffs.
- Create clean interfaces for model, retrieval, and voice providers.
- Establish engineering practices for code review, testing, observability, incident response, and production readiness.
Requirements
- 8+ years of software engineering experience, including 3+ years building and operating production AI or LLM-powered products.
- A bachelor's degree in Computer Science, Engineering, or a related technical field with 6+ years of professional experience, or a master's degree with 4+ years of professional experience in backend software engineering and Generative AI.
- A proven track record designing, building, and scaling distributed, production-grade systems.
- Production experience designing and shipping multi-agent or agentic workflows, including orchestration, tool use, state management, and failure handling.
- Strong Python skills and experience building production APIs and backend services; TypeScript experience is useful.
- Hands-on experience with cloud-native deployment, containers, Kubernetes, CI/CD, and production observability.
- Production experience with Azure and/or Databricks.
- Practical experience creating LLM evaluation test sets, measuring quality and accuracy, analyzing failures, and using results to improve systems or gate releases.
- Experience with retrieval-augmented generation, embeddings, vector databases, or large-scale search systems.
- Experience addressing unsupported answers, prompt injection, unsafe tool calls, and data-access boundaries through system design and code.
- Experience operating services with production requirements for reliability, latency, and cost.
- Product judgment, including scoping useful first versions, comparing approaches with evidence, and shipping iteratively.
- Preferred experience with LangGraph, LangChain, or similar agent and orchestration frameworks.
- Preferred experience with Databricks data, machine learning, or deployment workflows.
- Preferred experience with real-time or streaming systems such as WebSockets, WebRTC, audio pipelines, or other low-latency services.
- Preferred voice AI experience involving telephony platforms, speech-to-text, text-to-speech, turn-taking, or voice-agent frameworks.
- Preferred knowledge graph or large-scale information retrieval experience.
- Preferred experience in regulated or compliance-sensitive industries such as healthcare or finance.
- Preferred experience with LLM-as-judge methods, human review workflows, or production monitoring for AI quality.
Benefits
- Hybrid role based in the Toronto office.
- Paid time off.
- Comprehensive benefits plan.
- Company RRSP match.
- Development opportunities through the LinkedIn Learning platform.
Tech Stack
Categories
About Guidepoint
Guidepoint provides on-demand expert consultations, surveys, events, and custom research that help investors, consultants, and corporate teams make informed decisions. It operates a large global network of subject-matter experts and offers access via subscriptions and project-based engagements. Founded in 2003 and headquartered in New York, the privately held company serves sectors including healthcare, consumer goods, technology, media and telecom, and energy.