Agentic AI Developer

Posted 22 Days Ago
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Toronto, ON, CAN
In-Office
Mid level
Fintech • Consulting
The Role
Design, build, and deploy production-grade agentic multi-agent systems and stateful workflows. Implement memory and vector-based RAG pipelines, secure tool integrations, and cloud-deployed agents. Optimize LLM orchestration, enforce regulatory security and guardrails, collaborate with DevOps/RPA teams (UiPath), and maintain high code quality in Python/TypeScript.
Summary Generated by Built In

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 Yonge

Function:

Function - Tech Dev and Client Services

Schedule:

Full time

Skills Required

  • 3+ years professional experience building production-grade AI/ML applications with recent LLM orchestration and autonomous agent patterns
  • Proficiency in Python or TypeScript
  • Production-level experience with agentic frameworks or graph-based orchestration such as LangGraph or Google ADK
  • Practical experience with RAG pipelines, semantic search, and vector databases
  • Mastery of JSON Schema design and structured decoding for reliable LLM function-calling
  • Strong understanding of asynchronous programming, API design, and microservices architecture
  • Experience containerizing, deploying, and scaling AI agents in cloud environments and collaborating with DevOps
  • Designing agent workflows that meet enterprise security, compliance, and data governance standards with auditable logs
  • Experience bridging RPA (UiPath) with generative AI / intelligent automation
  • Prior experience deploying AI in regulated industries or live production agentic workflows
  • Commitment to software engineering best practices, code reviews, and producing clean, modular code

Equifax Inc. Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Equifax Inc. and has not been reviewed or approved by Equifax Inc..

  • Retirement Support Savings programs include a 401(k) with company matching and, in some contexts, profit-sharing or pension components. These are described as solid parts of the total package.
  • Parental & Family Support Programs include paid parental leave for birth and non-birthing parents and adoption assistance. Company materials highlight these benefits as part of a family-supportive offering.
  • Flexible Benefits Multiple medical plan choices, dental and vision options, FSAs/HSAs, and voluntary supplemental coverages enable customization. The company publishes plan summaries and SPDs to help compare cost and coverage by location and tier.

Equifax Inc. Insights

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The Company
HQ: Atlanta, GA
16,742 Employees

What We Do

At Equifax (NYSE: EFX), we believe knowledge drives progress. As a global data, analytics, and technology company, we play an essential role in the global economy by helping financial institutions, companies, employers, and government agencies make critical decisions with greater confidence. Our unique blend of differentiated data, analytics, and cloud technology drives insights to power decisions to move people forward. Headquartered in Atlanta and supported by nearly 15,000 employees worldwide, Equifax operates or has investments in 24 countries in North America, Central and South America, Europe, and the Asia Pacific region. For more information, visit Equifax.com.

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