Agentic AI Developer
At a glance
Mid-level AI Engineering role at Equifax (External). Toronto · full-time · no salary stated · we estimate CA$106,250–CA$167,125.
Equifax (External) has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and test multi-agent workflows with LangGraph, Google ADK, or the internal agent and UiPath platforms
- Give agents short- and long-term memory using vector databases and custom checkpoints for extended tasks
- Connect agents to APIs, databases, microservices, and SaaS tools, then deploy them with cloud and DevOps teams
- Add human review points, security controls, audit logs, and safeguards against hallucinations or endless loops
- Review code and explain agent designs and risks to business leaders and project teams
What you bring
- At least three years building production AI or machine-learning applications, with recent focus on LLM orchestration and agents
- Strong Python or TypeScript skills, including asynchronous programming, API design, and microservices
- Production experience with custom agent loops or graph orchestration such as LangGraph or Google ADK
- Practical knowledge of advanced RAG, semantic search, vector databases, and JSON-based structured outputs
Who this fits
This hands-on engineering role suits someone who can turn unclear, multi-step tasks into structured agent workflows and prototype solutions. You'll work with infrastructure, product, business, DevOps, and automation teams. The position is based in Toronto.
From the employer
Synopsis of the Role
At Equifax, we are moving past passive AI chat interfaces to build the future of autonomous workflows. We are creating intelligent, self-correcting multi-agent systems that can navigate complex software environments, utilize external tools, and solve open-ended business problems with minimal human intervention. We are seeking a highly skilled Agentic AI Developer to be the core engineer constructing our next-generation AI workforce.
In this role, you will be the hands-on builder translating complex automation blueprints into production-grade, stateful agentic workflows. Working within our secure, globally integrated, and highly regulated architecture, you will push the boundaries of what autonomous systems can do—balancing cutting-edge LLM orchestration with absolute data security and deterministic guardrails.
What you will do
Core Agent Engineering & Creative Prototyping
Build Complex Agentic Loops: Develop, test, and deploy robust multi-agent architectures and stateful graph workflows using LangGraph, Google ADK frameworks with our internal agentic or UiPath platforms.
State & Memory Management: Implement advanced short-term and long-term memory systems, utilizing vector databases and custom checkpointing to ensure agents maintain flawless context across long-running, asynchronous tasks.
Creative Problem Solving: Apply a customer-centric, design-thinking lens to architecture challenges. You will actively design solutions and rapidly prototype creative, fact-based AI systems that solve ambiguous, non-linear business problems.
Optimize Model Execution: Optimize agentic loops for latency, context-window management, and token consumption, making strategic decisions on when to deploy multi-LLM orchestration, lightweight local models, or high-performance frontier LLMs.
Tooling, APIs & Cloud Deployment
Equip Agents with Tools: Build clean, secure integrations allowing LLMs to interact with internal APIs, databases, modern microservices, and third-party SaaS platforms via advanced function-calling.
Cross-Functional Collaboration: Partner directly with infrastructure, product, business and DevOps teams to containerize, deploy, and scale your AI agents securely within a cloud environment, ensuring smooth production delivery.
Bridge AI & RPA: Partner with our automation squads to integrate agentic decision-making with enterprise-grade UiPath workflows, effectively turning traditional RPA bots into intelligent, cognitive executioners.
Regulated Security & Code Quality
Code for a Regulated Space: Design agent workflows that strictly adhere to enterprise security, compliance, and data governance standards, ensuring auditable decision logs and safe handling of sensitive data.
Code Quality & Governance: Build and follow strict software development best practices. You will conduct rigorous code reviews for internal and vendor-delivered artifacts, maintaining a standardized, world-class global code repository.
Implement Guardrails: Build human-in-the-loop (HITL) overrides and strict operational guardrails into agent architectures to eliminate catastrophic hallucinations and prevent infinite execution loops.
Maintain Code Excellence: Write exceptionally clean, modular, and reusable Python/TypeScript code. Conduct rigorous code reviews for internal and vendor-delivered components to maintain a global standard.
Stakeholder Translation: Act as a technical translator, clearly articulating complex AI concepts, loop mechanics, and architectural risks to non-technical business leaders and project teams.
What Experience You Need
Experience: 3+ years of professional experience building production-grade AI/ML applications, with a heavy emphasis on LLM orchestration and autonomous agent patterns over the last 1–2 years.
Software Engineering Mastery: Strong proficiency in Python or TypeScript, with a deep understanding of asynchronous programming, API design, and microservices architecture.
Agentic Frameworks: Proven, production-level experience building custom agentic runtime loops or utilizing graph-based orchestration frameworks like LangGraph or Google Agent Development Kits (ADK).
RAG & Vector Infrastructure: Practical experience working with Advanced RAG pipelines, semantic search, and vector databases
Structured Outputs: Mastery of JSON schema design and structured decoding techniques for bulletproof LLM tool-calling.
Problem-Solving Mindset: A strong architectural intuition for breaking down ambiguous, multi-step human tasks into structured, programmatic agent prompts and loops.
What Could Set You Apart
Regulated Industry Background: Prior experience deploying AI or high-throughput software solutions within a highly secure or regulated industry.
Live production experience: Experience with deploying live AI solutions with Agentic workflows or GenAI solutions
UiPath & Intelligent Automation: A strong understanding of the UiPath ecosystem and experience bridging traditional RPA with generative AI models.
A proactive, self-motivated mindset with a passion for driving AI adoption across an organization to fundamentally change the way people work.
Demonstrated learning agility and a proactive approach to mastering new technologies.
This is a newly created position.
Primary Location:
CAN-Toronto-5700 YongeFunction:
Function - Tech Dev and Client ServicesSchedule:
Full time