2 hours ago
Montréal, CanadaSenior
Responsibilities
- Design, build, and optimize AI agents and multi-agent systems for reasoning, planning, retrieval, workflow automation, and task execution.
- Develop agentic workflows using LLMs, RAG, APIs, tools, enterprise knowledge sources, memory, orchestration, and decision-making capabilities.
- Prototype, test, and refine proofs of concept and MVPs that demonstrate measurable business value and can scale into production.
- Build reusable platform-ready components, prompts, connectors, orchestration patterns, evaluation flows, and knowledge integrations.
- Align solutions with the Global AI Platform architecture, tooling, deployment patterns, governance standards, and approved engineering practices.
- Operationalize AI solutions through testing, observability, monitoring, reliability controls, documentation, and production handoffs.
- Support onboarding of Canada AI use cases through discovery, fit-gap assessment, remediation, and readiness activities.
- Contribute reference architectures, code patterns, evaluation methods, playbooks, and development standards.
- Ensure solutions meet Responsible AI, security, privacy, compliance, model risk, governance, and monitoring requirements.
- Collaborate with Product, Data Science, MLOps, Technology, Risk, architecture, and business stakeholder teams.
Requirements
- Bachelor’s or master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
- Hands-on experience developing machine learning, generative AI, or agentic AI solutions in enterprise environments using governed and reusable delivery patterns.
- Strong Python and SQL skills with experience in AI application architecture, orchestration, retrieval, prompt design, evaluation, integration, and production monitoring.
- Experience with LLMs, RAG, vector search, embedding models, agent frameworks, API integration, cloud-native development, and MLOps/LLMOps practices.
- Ability to build secure, scalable, platform-ready AI solutions while collaborating across architecture, MLOps, product, risk, and business teams.
- Experience designing, evaluating, and monitoring production-grade AI agents or agentic workflows on an enterprise AI platform is preferred.
- Understanding of Responsible AI, model governance, security review, risk management, and production approval processes in regulated environments is preferred.
- Experience building reusable enterprise AI capabilities, moving prototypes to enterprise platforms, or working with SRE practices, observability, incident response, and production readiness is preferred.
- Familiarity with Azure, AKS, PostgreSQL, Key Vault, graph and vector databases, agent orchestration, automated red teaming, LLM-as-a-Judge evaluation, Akka SDK patterns, Java syntax, or financial services environments is preferred.
- Bilingualism in English and French is an asset; proficiency in both languages is required for successful candidates in Québec supporting clients outside Québec.
Benefits
- Hybrid working arrangement in Montreal, Quebec.
- Eligible employees receive customizable health, dental, mental health, vision, disability, life, AD&D, adoption/surrogacy, wellness, and employee/family assistance benefits.
- Retirement savings plans, including pension and a global share ownership plan with employer matching contributions, plus financial education and counseling resources.
- Paid holidays, vacation, personal and sick days, and statutory leaves of absence in Canada.
- Eligible employees may participate in incentive programs tied to business and individual performance.
- Flexible, inclusive environment with learning, career growth, well-being, and accommodation support.
Tech Stack
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