This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer based in Canada.
This is a hands-on senior individual contributor role focused on designing, building, and shipping production-grade agentic AI workflows at enterprise scale. You will spend most of your time writing code and shaping reliable AI systems rather than managing people. The role combines advanced AI engineering with architecture, observability, and platform reliability across a large digital experience ecosystem. You will work with technologies such as LangGraph, Temporal, Pydantic, and LangFuse to create stateful, multi-agent workflows. You will establish engineering standards around RAG, prompt management, context optimization, and tool calling. You will also mentor engineers through code reviews, pairing, and technical discussions while helping shape the evolution of the AI engineering practice.
Accountabilities
- Design, build, and ship production-grade AI solutions and agentic workflows as an active hands-on engineering contributor.
- Architect stateful, cyclic, and multi-agent workflows using LangGraph, Temporal, and Pydantic, with a focus on enterprise reliability, scalability, and maintainability.
- Establish and improve AI observability practices using LangFuse, including tracing, prompt versioning, evaluation, dataset-driven testing, and performance benchmarking.
- Define engineering standards and reusable patterns for agent design, retrieval-augmented generation (RAG), prompt management, context optimization, memory, and tool-calling strategies.
- Collaborate with product and platform teams to develop AI architectures that satisfy enterprise-level SLA, security, compliance, and reliability requirements.
- Evaluate emerging AI technologies, LLM providers, orchestration frameworks, and agentic development tools through structured benchmarking and experimentation.
- Contribute to the continuous improvement of AI engineering practices, development workflows, testing approaches, and production operations.
- Mentor other engineers through code reviews, technical pairing, architecture discussions, and knowledge sharing, without taking on traditional people-management responsibilities.
- Participate in customer-facing architectural reviews, technical discovery sessions, and roadmap discussions, clearly communicating AI capabilities and technical trade-offs.
Requirements
- 8+ years of professional software engineering experience, including at least 3 years building and operating AI agents in production environments.
- Strong hands-on expertise with LangGraph, Temporal, and Pydantic, particularly for stateful, cyclic, and multi-agent workflows at enterprise scale.
- Hands-on experience with LangFuse or comparable AI observability platforms, including tracing, evaluation, prompt management, and dataset-driven testing.
- Experience with agent orchestration frameworks such as LangChain, LlamaIndex, CrewAI, or similar technologies, including chains, tools, memory, and retrieval pipelines.
- Deep proficiency in Python and strong software engineering fundamentals covering architecture, automated testing, CI/CD, code quality, and production reliability.
- Experience deploying AI systems in AWS, Azure, or GCP, including containerization and management of inference and infrastructure costs.
- Strong understanding of RAG architectures, vector databases, embedding models, retrieval strategies, and related AI system design considerations.
- Bachelor's degree in Computer Science or equivalent practical engineering experience.
- Familiarity with enterprise SaaS or content management platforms is an asset, as is experience with Drupal-based digital experience ecosystems.
- Fluency with AI-assisted development tools such as GitHub Copilot, Cursor, Claude, or comparable technologies, with the ability to incorporate AI into everyday engineering workflows.
- Exposure to persistent agent runtimes, cross-session memory, autonomous agent capabilities, and always-on agent infrastructure is a plus.
- Experience with LLM fine-tuning, model evaluation, foundational model trade-offs, and human-in-the-loop agent architectures is desirable.
- Strong communication skills, with the ability to explain sophisticated AI architectures and technical trade-offs to engineers, product leaders, and executive stakeholders.
- Demonstrated senior individual-contributor experience, with a reputation for high-quality code, strong system designs, technical ownership, and organic mentorship.
- An AI-native mindset, strong adaptability, intellectual curiosity, and a builder mentality, with a willingness to continuously rethink traditional workflows through AI and automation.
Benefits
- Competitive healthcare coverage designed to support employees and their families.
- Wellness programs supporting physical and mental well-being.
- Flexible paid time off that can be used when needed.
- Parental leave benefits.
- Employee recognition programs.
- Opportunities to work with advanced AI technologies and emerging agentic architectures.
- Professional growth through exposure to complex enterprise-scale engineering challenges.
- A collaborative environment that values innovation, continuous learning, and responsible adoption of AI.
- Equal opportunity and an inclusive workplace committed to providing fair access to employment opportunities and resources.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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