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. 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. You’ll 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. You’ll design end-to-end agentic AI architectures including planning loops, memory management, tool integration, and agent coordination patterns. You’ll 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. You’ll design and implement Model Context Protocol (MCP) server integrations for tool use, data access, and cross-system interoperability with enterprise systems. You’ll build advanced retrieval-augmented generation (RAG) systems including vector databases, embedding strategies, chunking optimization, hybrid search, re-ranking, and multi-source data synthesis. You’ll design and deliver AI and ML solutions across AWS, Azure, and GCP, using the right mix combination of cloud-native data services, ML tooling, LLM platforms, and software engineering practices. You’ll build in Python and, where useful, other languages to deliver machine learning systems, APIs, evaluation harnesses, retrieval pipelines, agent workflows, and production services. You’ll recommend and implement architecture for model and agent pipelines, CI/CD, testing, deployment, observability, andMLOps/LLMOpsat scale. You’ll implement evaluation frameworks (e.g., RAGAS,DeepEval,LangSmith) to measure task success rates, tool-call accuracy, and reasoning integrity for GenAI systems. You’ll build guardrails for safety, compliance, and performance monitoring including human-in-the-loop (HITL) approval workflows, escalation policies, and sandbox isolation. You’ll define AI governance frameworks including model risk management, responsible AI practices, regulatory compliance, and authorization boundaries for autonomous decision-making. You’ll explain model and system behavior to both technical and non-technical audiences, including leading deep technical presentations, workshops, and architecture conversations. You’ll collaborate with Product Owners to apply Slalom’s agile process and lead the initiation, delivery, and transition of projects in a client-facing role. You’ll lead and mentor engineers and machine learning practitioners. You’ll lead smaller projects (3 to 5 people) as the technical lead from project initiation to delivery. You’ll build trusted relationships with customers and collaborate across Slalom teams to share learnings and strengthen the broader Intelligence Engineering practice. You’ll be delivery-focused approximately 85–95% of the time. You’ll be willing to travel up to 50%, at peak times. You’ll work in a hybrid/office environment, with expectations for on-site work as needed.

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. You’ll be required to complete a background check.

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 cloud AI platform, such as AWS Bedrock, Azure AI Foundry/OpenAI Service, GCP Vertex AI/Gemini, or Databricks; experience operating and maintaining production environments is a plus
• Experience with AI-assisted development tools such as Claude Code, Cursor, Kiro, or similar IDE-based coding agents, including effective use for code generation, refactoring, debugging, and developer workflow acceleration
• Strong Python development skills; experience with FastAPI, Flask, or equivalent API frameworks
• Experience building ML or AI systems end to end, including data access, feature or retrieval flows, APIs, testing, deployment, and production support
• Familiarity with evaluation frameworks, tracing, observability, model behavior analysis, and regression testing for GenAI systems
• Understanding of prompt engineering, LLM fine-tuning, chain-of-thought reasoning, and structured output techniques
• Recognized as an authority on at least one technical domain (e.g., Agentic Systems, RAG, Multi-Agent Orchestration) with generalist familiarity across AI/ML
• Experience with Model Context Protocol (MCP) server development and integration (preferred)
• Experience with MLOps/LLMOps pipelines, CI/CD for ML, and model monitoring/observability (preferred)

Slalom Employee Perks:

• Culture & fun!

• Lunch & learns

• Health & wellness activities

• Holiday parties

• Employee community groups

• Social clubs & activities

• Vacation (20 days prorated based on start date & wellness/sick days)

• Tangible perks:

• Competitive compensation package

• $100 cell phone monthly reimbursement

• Registered Retirement Program (RRSP) & Employer Matching

• Tax-Free Savings Account (TFSA)

• Annual “Thrive Well-Being” Gift Card

• Family planning/ Fertility Benefit

• Maternity/Parental Leave Top-Up

• Medical & Dental Benefits

• Life and AD&D Insurance

• Access to Supplementary Life and AD&D Insurance

• Access to the Employee Assistance Program (EAP) and Inkblot Therapy

• And more!