Applied AI Engineer building evaluation pipelines, production agents, and reliable clinical AI for Tali’s healthcare platform. Owning models, retrieval, routing, and observability across ambient scribe, billing, search, and clinical workflows.
About the role
- Staff AI Engineer building and deploying enterprise AI applications for EQ Bank. Designing scalable systems, integrating LLMs, and delivering production solutions in Toronto.
Responsibilities
- Design, develop, and deploy AI-powered applications and workflows
- Write production-quality backend services, APIs, AI orchestration layers, agents, and enterprise integrations
- Rapidly prototype solutions and iterate them into scalable production systems
- Own delivery end-to-end: build, test, deploy, monitor, and improve
- Translate use cases into clear, implementable system designs
- Make architecture decisions balancing delivery speed, scalability, reliability, cost, and operational efficiency
- Define API-first integration, AI orchestration, workflow, reusable service, and component patterns
- Embed LLM capabilities into products, internal tools, and business processes
- Build and maintain APIs and system integrations
- Implement agent workflows and orchestration logic
- Optimize systems for performance, resilience, and cost efficiency
- Work directly with stakeholders to understand problems and validate solutions
- Translate requirements into working software quickly
- Iterate based on feedback and usage to drive measurable impact
- Build and contribute to shared libraries, templates, and services
- Establish practical patterns based on real implementations
- Evolve internal platforms through code and working solutions
- Implement secure and reliable AI solutions, including prompt safety, validation, injection/misuse prevention, observability, and traceability
- Align implementations with enterprise security, privacy, and compliance requirements
Requirements
- 8+ years of software engineering experience building and delivering scalable, production-grade applications and platforms
- Demonstrated success leading complex technical initiatives from design through deployment and ongoing operations
- Strong engineering fundamentals and ability to influence technical direction across teams and organizations
- Deep expertise designing scalable, resilient, and maintainable software architectures
- Experience balancing delivery speed vs. scalability and simplicity vs. flexibility
- Ability to move between coding and design thinking
- 3+ years of hands-on experience building and deploying AI/Generative AI solutions in production environments
- Strong understanding of prompt design and evaluation
- Strong understanding of agent-based workflows and orchestration
- Strong understanding of integrating AI into production systems
- Ability to debug, tune, and improve AI behavior in code
- Experience with Microsoft Azure, Claude, enterprise-approved LLMs, API-first architecture, event-driven architecture, and modular services
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Degree requirement
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