Senior Consultant - AI Engineer

Keyrus Canada • Montreal, QC

43d • CA$90,000 - CA$135,000 • Hybrid

About The Position

As a Senior Consultant - AI Engineer, you will architect and deliver enterprise AI solutions that move beyond experimentation into production-ready systems. Combining software engineering excellence with consulting expertise, you will design intelligent architectures, build agentic workflows, and guide organizations through the adoption of scalable, reliable, and measurable AI capabilities.
Translate business objectives into AI solutions by collaborating directly with executives, business leaders, and technical stakeholders to define success metrics and measurable outcomes
Evaluate AI platforms and recommend the most appropriate technology stack based on integration, governance, scalability, cost, and time-to-value considerations
Architect Agentic AI and Generative AI solutions including multi-agent workflows, RAG pipelines, tool/function calling, memory management, guardrails, and human-in-the-loop orchestration
Build production-grade AI agents and intelligent automations using LangChain, LangGraph, Bedrock AgentCore, and modern orchestration frameworks integrated with enterprise systems through APIs
Design evaluation pipelines, observability frameworks, prompt lifecycle management, and versioning strategies that maximize reliability, performance, and governance
Deliver Proofs of Concept, demonstrations, and production deployments supported by modern AI Engineering, CI/CD, and MLOps practices
Contribute to pre-sales initiatives by shaping solution offerings, supporting proposals, and providing technical credibility during client engagements
Mentor engineers and junior team members while defining reusable architectures, engineering standards, and AI best practices
Continuously evaluate emerging models, frameworks, MCP capabilities, and agent protocols to strengthen client solutions and Keyrus' AI practice

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field—or equivalent professional experience
• 5+ years of experience in Software Engineering, AI Engineering, or Data Engineering, including hands-on experience delivering Generative AI or Agentic AI solutions into production
• Experience working within consulting or client-facing environments is highly valued
• Strong Python development skills and solid software engineering fundamentals including APIs, microservices, version control, testing, and modular architecture
• Hands-on experience building AI agents and tool-enabled LLM applications using orchestration frameworks such as LangChain, LangGraph, or equivalent technologies
• Practical experience with AWS AI services, especially Amazon Bedrock, Bedrock Agents, Guardrails, and the broader AWS ecosystem including Lambda, API Gateway, S3, and IAM
• Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, chunking strategies, hybrid and semantic search, reranking, evaluation methodologies, and vector databases
• Experience evaluating AI platforms objectively and designing architectures that balance business value, technical feasibility, governance, and cost
• Knowledge of production AI engineering practices including observability, prompt management, evaluation pipelines, CI/CD, and MLOps
• Experience integrating enterprise AI solutions with CRM, ERP, and other business systems through APIs and modern cloud architectures
• Excellent communication skills, with the ability to engage both technical teams and executive stakeholders
• Comfortable translating complex AI architectures into practical business solutions and clear technical roadmaps
• Brings a consultative mindset that balances innovation with governance, scalability, and measurable outcomes
• Demonstrates ownership, structured problem-solving, and strong engineering judgment across the full AI lifecycle
• Builds credibility through collaboration, mentorship, and continuous technical excellence
• Thrives in environments where learning, experimentation, and production delivery coexist

Nice To Haves

• AWS AI/ML, AWS Solutions Architect, Salesforce Agentforce, or equivalent certifications are considered an asset
• Hands-on experience with Salesforce Agentforce and Data Cloud / Data 360
• Experience comparing and integrating multiple AI agent platforms within enterprise architectures
• Familiarity with Responsible AI, model governance, security, and enterprise guardrails
• Experience using Anthropic Claude, Claude Code, Claude Skills, Plugins, and MCP servers
• Industry experience in Financial Services, Retail, Supply Chain, or Healthcare
• Knowledge of regulatory and privacy frameworks such as GDPR
• Exposure to React or modern frontend frameworks for AI copilots and interactive demonstrations

Responsibilities

• Architect and deliver enterprise AI solutions that move beyond experimentation into production-ready systems.
• Design intelligent architectures, build agentic workflows, and guide organizations through the adoption of scalable, reliable, and measurable AI capabilities.
• Translate business objectives into AI solutions by collaborating directly with executives, business leaders, and technical stakeholders to define success metrics and measurable outcomes.
• Evaluate AI platforms and recommend the most appropriate technology stack based on integration, governance, scalability, cost, and time-to-value considerations.
• Architect Agentic AI and Generative AI solutions including multi-agent workflows, RAG pipelines, tool/function calling, memory management, guardrails, and human-in-the-loop orchestration.
• Build production-grade AI agents and intelligent automations using LangChain, LangGraph, Bedrock AgentCore, and modern orchestration frameworks integrated with enterprise systems through APIs.
• Design evaluation pipelines, observability frameworks, prompt lifecycle management, and versioning strategies that maximize reliability, performance, and governance.
• Deliver Proofs of Concept, demonstrations, and production deployments supported by modern AI Engineering, CI/CD, and MLOps practices.
• Contribute to pre-sales initiatives by shaping solution offerings, supporting proposals, and providing technical credibility during client engagements.
• Mentor engineers and junior team members while defining reusable architectures, engineering standards, and AI best practices.
• Continuously evaluate emerging models, frameworks, MCP capabilities, and agent protocols to strengthen client solutions and Keyrus' AI practice.

Benefits

• Group insurance for you and your family members
• RRSP and DPSP participation plans
• Monthly Wellness Allowance
• Telecommunication reimbursement
• Flexible work-from-home policy
• 4 weeks of paid vacation
• Language courses (French & English)
• Access to continuous learning through conferences, certifications, training programs, and industry events
• Individual development plans and coaching opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree