Industry Consultant

Zafin•Toronto, ON

8h•Hybrid

About The Position

Zafin is an AI platform company helping regulated institutions modernize how critical work is designed, governed, and delivered. Our technology enables organizations to move faster while maintaining the governance, accountability, and control required in highly regulated environments. Our portfolio includes Zafin AIOS, an agent orchestration platform for governed AI work; the Zafin Banking Platform, which helps banks modernize product, pricing, offers, billing, loyalty, and relationship management; and Zafin IO, an integration platform that connects data, systems, and workflows across complex enterprise environments. Headquartered in Toronto, Canada, Zafin partners with leading financial institutions across North America, Europe, the Middle East, Africa, and Asia-Pacific. As AI transforms the future of financial services, we're building the platforms that help regulated organizations adopt AI responsibly and at scale. What’s the Opportunity? The Industry Consultant applies banking and financial services expertise directly to the design of AI agent behavior. This role defines the business rules, policies, and exception logic that AI agents must operate against, and partners with client subject-matter experts to redesign workflows for combined human and AI agent execution. The output of this role is not documentation for reference — it is the operational logic an autonomous AI agent will execute in a production, regulated banking environment. This role becomes the trusted authority on how the client's business operates, translating workflows, business policies, decision logic, exception handling, and success measures into operational logic that AI agents can reliably execute. The Industry Consultant anchors the Discover and Design phases of the AIOS delivery journey. While the Client Engagement Lead owns the client relationship, the Domain Strategist owns the precision of business intent, reflecting the platform principle that unclear intent carries greater delivery risk than limited engineering capacity. Every business rule, exception, and success metric defined in this role directly shapes AI agent behavior in production. It also bridges business strategy, domain expertise, and AI solution design, ensuring AI agents reflect real business intent rather than generalized assumptions or technology-first implementations.

Requirements

5–10+ years of experience in banking operations, business analysis, or financial services consulting.
Business, Finance, or related field, or equivalent experience.
Substantial banking or financial services domain and process expertise.
Ability to translate business policy and exception handling into structured, AI agent-usable logic.
Experience with workflow redesign and identifying where automation adds genuine value.
Strong facilitation skills for extracting tacit knowledge from client subject-matter experts.
Understanding of why intent clarity is more critical in agentic AI delivery models than in traditional software delivery.
Strong understanding of operating model transformation, business process redesign, and organizational change within banking or other highly regulated environments.
Ability to facilitate executive and operational workshops that translate business priorities into AI-enabled operating models.
Working knowledge of AI, automation, and decision intelligence concepts sufficient to translate business requirements into AI agent behaviours.

Nice To Haves

Experience with AI-driven automation or large-scale enterprise IT transformation.
Experience authoring or reviewing business rules later encoded into software or automated systems.
Lean, Six Sigma, BPMN or similar process improvement methodologies

Responsibilities

Define the business rules, policies, and exception-handling logic that AI agents must operate against.
Partner with client stakeholders to redesign workflows for combined human and AI agent execution.
Identify, prioritize, and quantify opportunities for AI-driven automation and augmentation by evaluating business value, feasibility, operational risk, and client readiness.
Engage and build trusted relationships directly with client subject-matter experts, business leaders, and operations teams to capture domain knowledge, validating operating practices, and resolve business ambiguity.
Facilitate discovery workshops with client stakeholders to identify business priorities, operating constraints, pain points, opportunities, and measurable success criteria.
Lead definition of intent, constraints, and success metrics that anchor the Discover phase.
Partner with Agent Engineering to translate business logic into effective AI agent design.
Validate that AI agent behaviour reflects actual operating policy rather than generalized assumptions.
Participate in the Design phase, shaping human and AI agent workflows, decision points, and escalation paths.
Facilitate business process redesign sessions that optimize collaboration between human teams and AI agents while maintaining governance and operational integrity
Support evaluation cycles and user acceptance activities by confirming whether AI agent behavior in each scenario is accurately reflecting intended business need, decision per policy.
Validate proposed AI agent behaviours through business scenario walkthroughs and policy reviews prior to implementation.