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Ernst & Young

Global professional services: consulting, assurance, tax

AI and Data - Manager, AI Engineer

Applied Machine LearningUpdated on Nov 14
Full-timeCalgary, AB, Canada$110k - $160kIn-person

About the Job

Requirements

  • A degree in Computer Science, Data Science, Engineering, or a related technical discipline is required; an MSc or PhD is an advantage.
  • At least 5–8+ years of AI development experience, including at least 2 years building and maintaining production-grade AI/ML or agentic AI solutions.
  • Hands-on experience developing machine learning and deep learning algorithms at scale.
  • Deep experience with AI/ML libraries and frameworks.
  • Understanding of foundational statistics and mathematical modeling.
  • Advanced object-oriented coding skills in Python for production-level codebases.
  • Familiarity with Java, TypeScript, or JavaScript is a plus.
  • Hands-on experience building and deploying AI agents and AI/ML solutions.
  • Hands-on experience with containerization using Docker and Kubernetes, CI/CD pipelines, and version control for AI systems; working knowledge of LLM observability and monitoring tools.
  • Experience in API integration and development.
  • Deep experience designing and building agentic AI systems in enterprise environments.
  • Ability to troubleshoot AI-specific failure modes, including model hallucinations, retrieval gaps, context overflow, agent looping, and system latency, and engineer reliable solutions.
  • Experience with AI governance, model risk management, and regulatory considerations in complex or regulated industries.
  • Ability to adapt to evolving AI frameworks, agentic tool patterns, LLM capabilities, and cloud platform services.

Responsibilities

  • Design and implement production-grade agentic AI workflows using open frameworks such as LangGraph and CrewAI, proprietary cloud-based agentic platforms, agent orchestration, AI gateways such as MCP and A2A, observability, controls, and guardrails.
  • Build and optimize retrieval pipelines for Retrieval-Augmented Generation (RAG) and agentic workflows, including chunking strategies, embedding models, vector store integration, and re-ranking to ground agent outputs in accurate, current enterprise data.
  • Develop and integrate generative and agentic AI solutions using large and small language models (LLMs and SLMs).
  • Build evaluation frameworks to measure AI solution quality and consistency, and implement telemetry and monitoring to track model drift, latency, output quality, and cost metrics in production.
  • Use machine learning and deep learning algorithms and foundational statistical concepts to solve real-world AI/ML problems at scale.
  • Implement MLOps and LLMOps best practices across experimental and production environments, including deploying AI pipelines and microservices into cloud environments, APIs, and CI/CD to ensure high availability and low latency.
  • Build AI governance and responsible AI controls for AI systems.
  • Mentor junior team members and contribute to EY AI assets, accelerators, delivery standards, and go-to-market offerings in AI/ML, agentic AI, and generative AI.
  • Work across complex client engagements to design and implement AI/ML and agentic AI solutions end to end.
  • Work with business stakeholders, the AI Architect, AI Platform Engineers, and Data Scientists to translate business challenges into practical, scalable, and responsible AI solutions.
  • Influence executive stakeholders and help clients responsibly adopt agentic AI to drive measurable business outcomes.

Desired Qualifications

  • Consulting or professional services experience is strongly preferred.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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