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Slalom

Agentic AI Architect - Intelligence Engineering (Toronto)

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 15, 2026
Posting language: English
Posted: Oct 16, 2026

Original job description

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 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 withFastAPI, 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 techniques
Ability to work across new domains and unfamiliar data structures and lead exploratory analysis when requirements are not fully defined
Excellent verbal and written communication skills; ability to lead highly technical presentations
Familiarity with Agile project delivery
(Preferred) Experience with Model Context Protocol (MCP) server development and integration
(Preferred) Experience with MLOps/LLMOps pipelines, CI/CD for ML, and model monitoring/observability

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!

*All benefits are subject to eligibility requirements

Slalom is an inclusive, equal opportunity employer dedicated to building a diverse workforce. We encourage applications from all qualified candidates and will work to reasonably accommodate applicants’ needs throughout all stages of the recruitment and selection process. Please advise the talent acquisition team if you require accommodations during the interview process. At Slalom, we leverage artificial intelligence (AI) to enhance the efficiency and scalability of our recruitment process. To learn more about how we leverage AI please read our TA AI Usage policy here.

Please note if you are hired at Slalom you will be required to complete a background check.

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More about this job

Responsibilities

Design and deliver secure, scalable AI/ML and agentic AI solutions, including multi-agent orchestration, RAG pipelines, MCP integrations, cloud-native services, and governance frameworks. Lead client-facing technical delivery and project initiation, mentor engineers, communicate architecture decisions, and help clients adopt practices that sustain long-term value.

Requirements

Candidates need at least five years of software engineering experience, including two or more years focused on generative AI, LLMs, or agentic AI, along with hands-on experience building production AI systems. Strong Python skills and experience with agent frameworks, RAG, cloud AI platforms, evaluation and observability, and technical communication are required; Agile delivery, MCP, and MLOps/LLMOps experience are preferred.

Skills

Agentic AI Architecture
Multi-Agent Systems
Generative AI
Retrieval-Augmented Generation
Python
Cloud Architecture
AWS
Azure
Google Cloud Platform
Model Context Protocol
AI Governance
MLOps And LLMOps
AI Evaluation And Observability
FastAPI
Technical Leadership
Agile Project Delivery

Benefits

Lunch And Learns
Health And Wellness Activities
Holiday Parties
Employee Community Groups
Social Clubs And Activities
20 Days Of Vacation
Wellness And Sick Days
Competitive Compensation
Cell Phone Reimbursement
Registered Retirement Savings Plan With Employer Matching
Tax-Free Savings Account
Annual Well-Being Gift Card
Family Planning And Fertility Benefits
Maternity And Parental Leave Top-Up
Medical Benefits
Dental Benefits
Life And Accidental Death And Dismemberment Insurance
Supplementary Life And Accidental Death And Dismemberment Insurance
Employee Assistance Program
Therapy Access

Visa sponsorship

Not detected in the job text

Keywords

Agentic AI
Artificial Intelligence
Machine Learning
Generative AI
Large Language Models
Multi-Agent Orchestration
LangGraph
Strands Agents SDK
OpenAI Agents SDK
Google ADK
Model Context Protocol
Retrieval-Augmented Generation
Vector Databases
AWS Bedrock
Azure AI Foundry
Azure OpenAI Service
Google Vertex AI
Gemini
Databricks
Python
FastAPI
RAGAS
DeepEval
LangSmith
MLOps
LLMOps
CI/CD
Human-In-The-Loop
Responsible AI
Agile

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