Agentic AI Architect - Intelligence Engineering (Toronto)

At Slalom, we co-create modern technology and software products with clients who are ready to accelerate their digital product development. We imagine how things can be made better, then set out to realize what’s possible—driving innovation with quality, resilience, and purpose. By blending design, product engineering, analytics, and automation, we build the custom-built software and data products of tomorrow.

Job Title:
Agentic AI Architect or Sr. Architect - Intelligence Engineering (For Vacant Role)

Mission
As a Senior Architect or Architect in Intelligence Engineering, you’ll design and deliver innovative AI/ML and agentic AI solutions as part of intelligent products and automating / re-envisioning human workflows on Amazon Web Services, Azure, and Google Cloud. This includes architecting multi-agent systems, LLM-powered autonomous workflows, retrieval-augmented generation (RAG) pipelines, and enterprise-grade AI governance frameworks using cutting-edge orchestration frameworks, tool-use protocols, and cloud-native AI services. You’ll help clients move from isolated proofs of concept to secure, scalable, observable systems that create real business value, while helping craft projects in their initial phases and delivering them with a team.

Who you’ll work with
You’ll join a tightly knit product team—engineers, product leaders, designers, and data practitioners—who co‑create modern software with our customers. We move from discovery to delivery together, pairing on code, pressure‑testing ideas with real users, and turning learnings into ship‑ready increments. You’ll collaborate with customer stakeholders and field teams to bring outside‑in insights into the roadmap, and you’ll help enable clients on the practices and tools we use so they can sustain value long after launch. Think craft‑driven Builders who care about outcomes, not just output.

What you’ll do
Provide thought leadership on AI/ML, Generative AI, and Agentic AI internally and with clients, while contributing to a culture of collaboration, learning, and curiosity
Design end-to-end agentic AI architectures including planning loops, memory management, tool integration, and agent coordination patterns
Architect multi-agent orchestration systems using frameworks such asStrands Agents SDK,OpenAI Agents SDK, Google ADK,LangGraphor similar for autonomous reasoning, decision-making, and task execution
Design and implement Model Context Protocol (MCP) server integrations for tool use, data access, and cross-system interoperability with enterprise systems
Build advanced retrieval-augmented generation (RAG) systems including vector databases, embedding strategies, chunking optimization, hybrid search, re-ranking, and multi-source data synthesis
Design and deliver AI and ML solutions across AWS, Azure, and GCP, using the rightmixcombinationof cloud-native data services, ML tooling, LLM platforms, and software engineering practices
Build in Python and, where useful, other languages to deliver machine learning systems, APIs, evaluation harnesses, retrieval pipelines, agent workflows, and production services
Recommend and implement architecture for model and agent pipelines, CI/CD, testing, deployment, observability, andMLOps/LLMOpsat scale
Implement evaluation frameworks (e.g., RAGAS,DeepEval,LangSmith) to measure task success rates, tool-call accuracy, and reasoning integrity for GenAI systems
Build guardrails for safety, compliance, and performance monitoring including human-in-the-loop (HITL) approval workflows, escalation policies, and sandbox isolation
Define AI governance frameworks including model risk management, responsible AI practices, regulatory compliance, and authorization boundaries for autonomous decision-making
Explain model and system behavior to both technical and non-technical audiences, including leading deep technical presentations, workshops, and architecture conversations
Collaborate with Product Owners to apply Slalom’s agile process and lead the initiation, delivery, and transition of projects in a client-facing role
Lead and mentor engineers and machine learning practitioners. Lead smaller projects (3 to 5 people) as the technical lead from project initiation to delivery
Build trusted relationships with customers and collaborate across Slalom teams to share learnings and strengthen the broader Intelligence Engineering practice
Will be delivery-focusedapproximately 85–95% of the time
Willingness to travel up to 50%, at peak times

Hybrid/In office: We are hybrid but there are expectations that if your team leader requires you onsite that you are able to meet those expectations/requirements

Slalom is committed to fair and equitable compensation practices. For the role, we are hiring at the following levels and targeted base pay salary ranges:

Architect - CAD123,000 to CAD163,000
Sr. Architect - CAD147,000 to CAD195,000

In addition, there is potential for a 10% discretionary bonus for Architect, and 12% for Sr. Architect, based on individual and company performance. Actual compensation will depend upon individual’s skills, experience, qualifications, and other relevant factors.

What you’ll do
5+ years of software engineering experience building and deploying production systems; experience with machine learning, applied AI, or intelligent software systems is a plus, with 2+ years focused on generative AI, LLMs, or agentic AI systems
Hands-on experience designing or building multi-agent systems including agent orchestration, tool integration, and autonomous decision-making workflows
Proficiency with at least one agentic AI or workflow framework such as LangGraph, Strands, AutoGen, CrewAI, Semantic Kernel, OpenAI Agents SDK, Google ADK, or similar
Experience with RAG architectures including vector databases, embeddings, and retrieval optimization, and context management techniques such as chunking, summarization, and memory handling
Experience developing production-ready solutions on at least one major clou