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Toronto, Ontario, Canada
Hybrid
As a Principal Agentic Engineer, you will operate at the intersection of deep full-stack engineering craft and AI-native delivery. This is an L5 principal-level role where you own the technical vision across the entire stack for complex, enterprise-scale systems, while simultaneously driving APPLY's agentic delivery model: architecting, orchestrating, and directing teams of coding agents to accomplish implementation at speed and scale.
You are comfortable moving fluidly across frontend, backend, APIs, data layers, and cloud infrastructure. You are not expected to be a specialist in any one layer, you are expected to be dangerous across all of them. You turn ambiguous product and business goals into shipped, production-ready software, mentor engineers across the organization, and bring together composable platforms, cloud infrastructure, and AI-powered experiences into cohesive, scalable solutions. This is not a hands-off leadership role. You will lead by doing, and by raising the technical bar around you.
In this role, you can also expect to be on projects as part of our FDAIC team (Forward Deployed AI Consultant). This is a multidisciplinary team that includes representation from other departments such as CX, Strategy and Product, all of whom are AI-first in the delivery of their duties. This team does short engagements to uncover areas of growth for Apply within the client, while delivering on near term goals.
Full-Stack Architecture & Technical Vision
Envision and architect end-to-end solutions for complex, enterprise-scale projects — spanning frontend, backend services, APIs, data pipelines, and cloud infrastructure.
Provide clear technical direction across the full stack; ensure quality, coherence, and alignment of all technical solutions with business objectives.
Champion the design and implementation of highly scalable, secure, and maintainable software systems — API-first, cloud-native, and composable by default.
Own technical decisions across layers: from UI and component architecture to service design, data modelling, and infrastructure configuration.
Guide technology decisions that align with both business objectives and Apply's standard of engineering excellence.
Agentic Engineering & AI-Native Delivery
Organize, distribute, and translate backlog requirements into detailed, spec-driven requirements that coding agents can implement autonomously.
Synthesize user stories, site maps, content strategy, design systems, and brand strategy into specifications that guide agent-driven development.
Apply spec-driven development (e.g. BMAD Method or equivalent) to ensure clarity, consistency, and quality across agent-orchestrated workflows.
Architect full-stack solutions, across UI, APIs, services, and data stores, that integrate seamlessly with AI-powered systems, including LLM APIs, RAG pipelines, and agent orchestration frameworks.
Design both user-facing experiences and backend service contracts that help products express goals, constraints, and context clearly to AI agents.
Integrate AI-powered APIs, LLM-driven features, RAG-based experiences, and AI-assisted developer workflows throughout the full application stack.
Platform, Cloud & Composable Architecture
Design and implement microservices, APIs, and composable architectures using modern cloud platforms (GCP preferred; AWS/Azure experience valued).
Build and maintain backend services, data pipelines, and integrations with composable platforms: Contentful, Contentstack, Algolia, Cloudinary, commercetools, and similar MACH ecosystem products.
Implement enterprise-grade design systems, content models, component libraries, and the backend services that power them.
Ensure systems are performant and well-instrumented across all layers, from client-side rendering and GEO to API latency, caching, and data integrity.
Leverage containerization (Docker), orchestration (Kubernetes), serverless patterns, and infrastructure-as-code where appropriate.
Technical Leadership & Mentorship
Serve as a technical visionary, shaping the engineering culture and raising technical standards across multiple teams and practices.
Mentor and guide engineers in best practices: architectural decision-making, spec-driven development, AI-assisted workflows, and engineering craft.
Foster a culture of continuous learning, innovation, psychological safety, and engineering excellence.
Lead by example, demonstrating humility, curiosity, and deep professional commitment.
Collaboration & Communication
Collaborate with Technology Directors, Engineering Managers, Product, UX, and cross-functional stakeholders to shape and deliver solutions.
Partner with Project Managers and client stakeholders to manage delivery risks, timelines, and expectations.
Communicate complex technical and AI concepts clearly to varied audiences, from engineers to non-technical clients.
Influence across multiple teams and practices through technical leadership and collaborative synergy.
Engineering Experience & Foundation
10+ years of software engineering experience across the full stack, with demonstrated technical leadership at Staff or Lead level.
Proficiency in TypeScript and modern JavaScript; hands-on experience with React and Next.js on the frontend and Node.js or similar runtimes on the backend.
Proven ability to design, build, and maintain RESTful and/or GraphQL APIs and backend services, not just consume them.
Experience with relational and/or NoSQL databases: schema design, query optimization, and data modelling for production systems.
Deep understanding of API design, microservices, cloud-native architectures, and headless/composable systems (MACH principles).
Extensive experience with cloud platforms (GCP preferred; AWS or Azure also valued) and their associated services.
Experience with containerization (Docker), orchestration (Kubernetes), and serverless computing.
Familiarity with Git, CI/CD workflows, and production deployment practices.
Strong system design fundamentals across layers: API contracts, data flow, caching strategies, auth patterns, and performance optimization at scale.
Agentic & AI Capabilities
Hands-on experience working with AI coding agents (e.g. Claude Code, GitHub Copilot) in production delivery workflows.
Strong prompt engineering skills and ability to write high-quality agent specifications.
Demonstrated experience with LLMs (e.g. Claude Opus, Gemini, GPT-4/5) in real-world application development.
Experience with vector stores and RAG-powered applications.
Experience with Agent Development Kits (e.g. Google ADK) or similar orchestration frameworks.
Familiarity with Vertex AI, Google Gen AI APIs, or equivalent AI platform tooling.
Genuine curiosity and passion for Generative AI with a desire to make it a core focus of your career.
Leadership & Professional Skills
Proven track record of leading complex, enterprise-scale software projects with high autonomy.
Demonstrated ability to mentor and grow engineers, resolve technical conflicts, and drive alignment.
Exceptional communication skills, written and verbal, with the ability to explain complex concepts to non-technical stakeholders.
Strategic problem-solving ability with comfort navigating ambiguous goals and translating them into clear technical direction.
Experience working effectively in fully remote, distributed team environments.
Background in a consultancy or professional services firm is strongly preferred.
Experience with BMAD Method or similar spec-driven development frameworks.
Experience with AI agent design patterns, task planning, and reasoning.
Experience with agent observability and debugging.
Familiarity with layered and distributed architectures.
Experience with Terraform or infrastructure-as-code practices.
Experience across mobile, platform engineering, or testing domains in addition to full-stack web.
Experience with eCommerce platforms (e.g. commercetools, CommerceLayer) end-to-end, from storefront to order management APIs.
Familiarity with Lean and Agile principles and frameworks.
Experience contributing to business development and technical strategy initiatives.
Track record of driving innovation through emerging technology adoption.