Senior AI Engineer, IT Solutions 1

Celestica Inc.; Toronto; On-site; CAD 123,200 - 173,200; Full time

Job summary

Celestica Inc. seeks a Senior AI Engineer to drive AI/ML initiatives within IT Solutions, focusing on architecture, data pipelines, and production deployment. You will collaborate with business stakeholders to translate needs into scalable AI systems.

The role requires deep knowledge of Generative AI, vector databases, and end‑to‑end delivery from discovery to production. Strong Python, cloud AI services, and DevOps experience are essential.

Qualifications

• 11+ years of experience in IT, software engineering, or data science with a strong AI/ML focus.
• Strong knowledge of Generative AI and vector databases (e.g., Pinecone, Weaviate, Milvus).
• Ability to translate complex business challenges into scalable AI solutions and communicate with stakeholders.

Responsibilities

• Elicit and document AI/ML requirements from stakeholders across departments.
• Define technical feasibility, model architectures (LLMs/SLMs/ML) and success metrics.
• Design data ingestion pipelines for vector databases and RAG deployment.
• Implement MLOps CI/CD and monitoring for production AI models.

Skills

Python

LLMs

Prompt engineering

Vector databases

LangChain / LlamaIndex

MLOps / CI-CD

Data modeling

Education

Bachelor's or Master’s degree in Computer Science / AI / Data Science

Tools

Docker

Kubernetes

MLflow

Kubeflow

Job description

Senior AI Engineer, IT Solutions 1

Location: Toronto, ON, CA

Summary

We are seeking a highly motivated and technically proficient AI Engineer to join our growing Data & Analytics team. In this role, you will be a key liaison between business stakeholders and the technical AI team, translating complex business challenges into scalable artificial intelligence and machine learning solutions. You will be responsible for defining technical requirements, designing AI architectures (including Generative AI and RAG patterns), and collaborating with the Data Center of Excellence to deliver high‑quality, production‑ready AI tools that drive innovation and operational efficiency across the organization.

AI Solution Scoping & Requirements

Elicit and document technical requirements for AI and Machine Learning projects through workshops and deep dives with stakeholders across various departments.

Define the technical feasibility of proposed AI use cases, identifying appropriate model architectures (LLMs, SLMs, or traditional ML) and success metrics (Accuracy, F1‑score, Perplexity, etc.).

Analyze existing business processes to identify automation opportunities and areas where Generative AI can provide a competitive advantage.

Work with stakeholders to identify and prepare high‑quality datasets for model training, fine‑tuning, and grounding.

Design and implement data ingestion pipelines for vector databases, ensuring data integrity and optimal embedding strategies for Retrieval‑Augmented Generation (RAG).

Collaborate with data engineers to ensure scalable, secure, and compliant data flows between enterprise systems and AI models.

Develop, test, and refine AI prompts and orchestration workflows using frameworks like LangChain, LlamaIndex, or Semantic Kernel.

Evaluate and select appropriate foundation models (OpenAI, Anthropic, Llama, etc.) based on performance, cost, and latency requirements.

Translate business logic into technical specifications for API integrations, model endpoints, and user interfaces.

MLOps, Deployment & Monitoring

Implement MLOps best practices to ensure the continuous integration and deployment (CI/CD) of AI models.

Establish monitoring frameworks to track model performance, “drift,” and hallucination rates in production environments.

Ensure AI solutions adhere to corporate data governance, security, and ethical AI principles.

11+ years of experience in Information Technology, Software Engineering, or Data Science, with a significant focus on AI/ML development.

Strong understanding of Generative AI landscapes, including LLMs, prompt engineering, and vector databases (e.g., Pinecone, Weaviate, Milvus).

Proven ability to architect end‑to‑end AI solutions from discovery to production deployment.

Excellent communication skills, with the ability to explain complex technical AI concepts to non‑technical business leaders.

Advanced proficiency in Python and relevant libraries (NumPy, Pandas, PyTorch, or TensorFlow).

Experience with Cloud AI Services (Azure AI Studio, AWS Bedrock, or Google Vertex AI [Preferred]).

Knowledge of SQL and advanced data modeling for structured and unstructured data.

Familiarity with MLOps tools (MLflow, Kubeflow) and containerization (Docker, Kubernetes).

Experience working in an Agile/Scrum development environment.

Knowledge of AI security frameworks and responsible AI practices (e.g., OWASP for LLMs, MCP).

Industry experience in manufacturing or a related industrial sector.

Physical Demands

• Duties of this position are performed in a normal office environment.
• Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data. Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required.

Salary Range: $123,200 - 173,200 CAD. The stated range includes Base Salary and target Short‑Term Incentive (STI) compensation only. A comprehensive benefits package is offered in addition to this range. The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.

Typical Experience

11+ years of progressive experience in technical roles, with at least 3-5 years specifically focused on AI/ML engineering or architecture.

Proven track record of delivering production‑grade AI applications.

AI‑related certifications (e.g., Azure AI Engineer Associate, AWS Machine Learning Specialty) are highly preferred.

Typical Education

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field; or a robust combination of work experience and specialized AI certification.

Job Segment

Job Segment: Test Engineer, Computer Science, Manufacturing Engineer, Data Entry, Testing, Engineering, Technology, Administrative

Equal‑Opportunity Mandate

Celestica is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. At Celestica we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. Special arrangements can be made for candidates who need it throughout the hiring process.