Agentic AI Developer

Résumé du poste

The developer will build and deploy autonomous multi-agent systems and stateful workflows to solve complex business problems. They will also integrate these AI agents with internal APIs, cloud infrastructure, and UiPath automation platforms while ensuring strict security and compliance.

Détails du poste

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

Ce que vous ferez

The developer will build and deploy autonomous multi-agent systems and stateful workflows to solve complex business problems. They will also integrate these AI agents with internal APIs, cloud infrastructure, and UiPath automation platforms while ensuring strict security and compliance.

Exigences

Candidates must have 3+ years of professional experience in AI/ML application development with a focus on LLM orchestration and autonomous agents. Proficiency in Python or TypeScript and experience with agentic frameworks like LangGraph are required.

Compétences indiquées

• TypeScript · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• TypeScript
• LLM Orchestration
• LangGraph
• Agentic Workflows
• RAG
• Vector Databases
• API Design
• Microservices
• UiPath
• JSON Schema
• Cloud Deployment
• Software Engineering
• Autonomous Systems
• Data Governance
• Hallucinations
• Tool Calling
• Robotic Process Automation
• Software Solutions
• Cross-Functional Collaboration
• Agentic AI
• Langgraph
• Business Problems
• Pipelines
• Vector Database
• Strategic Decision Making
• Generative Artificial Intelligence
• Intelligent Automation
• Workflow Management
• Learning Agility
• AI Adoption
• Self-Motivation
• AI Agents
• Application Programming Interface (API)
• Multi-Agent Systems
• Artificial Intelligence
• Software Development
• Automation
• Autonomous System
• Management
• Decision Making
• Client Services
• Software As A Service (SaaS)
• Code Review
• Creative Problem Solving
• Data Security
• Design Thinking
• Deterministic Methods
• DevOps
• Memory Management

Domaines d’emploi

• Software
• Technology
• Data & Analytics
• Engineering
• UI Developer
• Software Developer / Engineer
• Software Developers