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Randstad Canada
Senior AI EngineerRandstad Canada • Toronto, Ontario, CA
Senior AI Engineer

Senior AI Engineer

Randstad Canada • Toronto, Ontario, CA
30+ days ago
Job type
  • Temporary
  • Quick Apply
Job description

We are seeking a highly accomplished Senior AI Engineer to spearhead the hands-on development, configuration, and structural optimization of enterprise-scale Artificial Intelligence, Generative AI, and Conversational AI solutions. In this role, you will take technical ownership of building next-generation cloud contact centre capabilities—transforming traditional IVR tracks into intelligent, autonomous self-service ecosystems. Operating deep within the AWS ecosystem, you will develop complex serverless data pipelines, engineer sophisticated Agentic AI frameworks, implement precise Model Context Protocol (MCP) server integrations, and deploy robust guardrails to deliver secure, context-aware, and highly performant customer interactions.

Location: Toronto, ON (Hybrid)

Duration: 9-month contract.



Advantages
Pioneering Cognitive Sandbox Access: Command a hands-on engineering role deploying highly innovative AI technologies, including Agentic AI and the cutting-edge Model Context Protocol (MCP).

High-Scale Cloud Autonomy: Build across a world-class AWS landscape, connecting deep learning model parameters directly with high-volume, real-time telephony pipelines.

Omnichannel Modernization Leadership: Drive visible digital transformation, converting legacy citizen engagement models into empathetic, intuitive, and secure conversational interfaces.

Visible Strategic Alignment: Expand your technical portfolio by aligning advanced AI product engineering with robust enterprise security, privacy, and public sector governance models.



Responsibilities
Generative AI & Agent Engineering: Architect, configure, and scale autonomous AI Agents utilizing foundational large language models (LLMs like Anthropic Claude, OpenAI GPT, and Google Gemini) combined with tool-calling and function-calling orchestration frameworks.

Knowledge Retrieval & RAG Architectures: Build and tune advanced Retrieval-Augmented Generation (RAG) structures, managing semantic search patterns, vector indexing, and pipeline connectivity into secure enterprise knowledge repositories.

Amazon Connect & Customer AI Integration: Design, implement, and optimize cloud-based contact flows and intelligent routing logic leveraging Amazon Connect and Amazon Connect Customer AI Agents.

Conversational IVR & Bot Development: Build production-grade Amazon Lex bots—defining intricate intents, slot mappings, conversational utterances, validation rules, and automated human-in-the-loop escalation workflows.

Prompt Engineering & Orchestration: Author, evaluate, and continuously refine prompt engineering templates, system instructions, and multi-turn dialog structures to maximize response accuracy and conversational flow.

AI Guardrail & Security Governance: Operationalize strict data defense metrics, content filters, grounding strategies, and response validation parameters to protect user privacy, prevent data leaks, and mitigate hallucinations.

Advanced Protocol (MCP) Server Integration: Develop and maintain Model Context Protocol (MCP) server connectors to safely expose internal databases, APIs, and business applications to autonomous LLM actors.

Serverless Infrastructure & API Development: Write and deploy secure serverless microservices and event-driven data workflows using Python, Node.js, AWS Lambda, API Gateway, Amazon DynamoDB, and Amazon S3.

Contact Center Analytics & Telemetry: Utilize Contact Lens and Contact Trace Records (CTR) to audit real-time conversation metrics, sentiment analysis, speech-to-text outputs, and operational KPIs for continuous pipeline tuning.

CI/CD & DevOps Automation: Manage source control branching and automated deployment operations via Git, GitLab, Jenkins, Infrastructure as Code (IaC), and automated unit/integration testing frameworks.



Qualifications
Core AI/ML Engineering Seniority: 5+ years of progressive professional experience designing, building, and deploying Artificial Intelligence, Machine Learning, or data engineering solutions within enterprise environments.

Generative AI & LLM Execution Depth: Proven, hands-on experience implementing Generative AI and Large Language Model (LLM) architectures, specifically managing RAG workflows, vector lookups, and model performance tuning.

Amazon Connect Cloud Platform Mastery: 5+ years of dedicated professional experience implementing and managing cloud contact centre frameworks utilizing Amazon Connect.

Amazon Connect Customer AI Agent & Lex Fluency: Practical background configuring Amazon Connect Customer AI Agents paired with expert-level proficiency developing Amazon Lex bots (intents, slots, fulfillment logic).

Core Development Tool Stack: Advanced, production-grade programming capability in Python, complemented by strong development experience with JavaScript, Node.js, and relational/NoSQL databases.

Full-Stack AWS Ecosystem Competency: Solid technical experience configuring core serverless and monitoring services, explicitly AWS Lambda, API Gateway, DynamoDB, S3, CloudWatch, and EventBridge.

Prompt Design & Tool-Calling Engineering: Proven capability crafting prompt templates, orchestrating function-calling hooks, and setting up content moderation safety guardrails.

Multi-Platform Analytics Awareness: Functional understanding of parallel AI ecosystems (Azure OpenAI, Azure AI Foundry, Google Vertex AI) along with contact center logging metrics (Contact Lens, CTRs).

Soft Skills: Outstanding analytical, troubleshooting, and critical-thinking capabilities, with a track record of collaborating across cross-functional squads and presenting technical findings to business teams.

Nice to Have:
Prior professional experience delivering complex conversational applications, I&IT project methodologies, or cloud-native architectures within a Canadian public sector framework or highly regulated space.

Foundational familiarity with machine learning model lifecycles via AWS SageMaker.

Basic operational awareness of digital accessibility regulations, including AODA and WCAG standards.



Summary
If you're interested in the "Senior AI Engineer" role based in Toronto, we encourage you to apply online at www.randstad.ca. Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!

Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.

Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.

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Senior AI Engineer • Toronto, Ontario, CA

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