At Slalom, we co-create up-to-date 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 as Strands Agents SDK, OpenAI Agents SDK, Google ADK, LangGraph or 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 right mix combination of 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, and MLOps/LLMOps at 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‑focused approximately 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 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 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

Culture & fun!

Lunch & learns

Health & wellness activities

Holiday parties

Employee community groupsSocial 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)

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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📌 Agentic AI Architect - Intelligence Engineering (Toronto) (Ontario)
🏢 Slalom
📍 Ontario