Agent Engineer
$80,000–$190,000 year
HybridToronto, Ontario, Canada
Job Summary
Build, configure, and optimize AI agents, workflows, prompts, tools, and integrations within the Zafin AI Operating System. Translate business rules and technical specifications into production-grade AI capabilities while designing data pipelines and conversational experiences. Execute the full delivery lifecycle from analysis through assisted deployment, ensuring reliability and integrating APIs, databases, and enterprise systems. Configure and troubleshoot production services, implement monitoring and observability, and contribute reusable components to the shared platform library. Partner cross-functionally with architects and consultants to refine agent behavior based on evaluation findings and client feedback.
Required Qualifications
- 1–10+ years of experience in software or AI engineering, automation, data engineering, or related technical roles
- Degree in Comp Sci, Comp Eng, Engineering, or other technical field, or equivalent or practical experience
- Proficiency in at least one relevant programming language, such as Python, TypeScript, or Java
- Understanding of software engineering fundamentals, including source control, testing, debugging, code review, APIs, data structures, and deployment practices
- Understanding of large language model fundamentals, prompt design, tool use, and common approaches for building AI-powered applications
- Experience or demonstrated ability building software applications, automation workflows, data-enabled systems, or AI solutions
- Familiarity with integrating APIs, enterprise applications, databases, and structured and unstructured data sources
- Understanding of testing and evaluation practices for AI-driven systems, including behavioural, reliability, and safety evaluation
- Familiarity with cloud-native applications, CI/CD, monitoring, logging, observability, and production-support practices
- Ability to interpret technical designs and translate them into maintainable working implementations
- Understanding of privacy, security, data governance, and responsible AI practices applicable to enterprise AI systems, particularly with regulated industries
- Strong analytical and debugging skills
- Familiarity with AI engineering and delivery metrics (pull request acceptance rate, autonomous merge rate, cost per accepted change) as core measures of engineering quality
Desired Qualifications
- Domain knowledge of banking, financial services, or large-scale enterprise IT environments
- Experience building internal AI tools or platforms adopted by other engineering teams
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