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Senior AI Engineer, IT Solutions

Remote / Online - Candidates ideally in
New York, New York County, New York, 10261, USA
Listing for: Celestica
Remote/Work from Home position
Listed on 2026-03-07
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Senior AI Engineer, IT Solutions 1
Location: New York

Req

Remote Position:
Hybrid

Region:
Americas

Country: USA

General Overview

Functional Area: Information Technology (ITM)

Career Stream: IT Solutions

Role: Technical Lead (TEL)

Job Title: Technical Lead, IT Solutions

Job Code: TL-ITM-SOLN

Job Level: Level 10

Direct/Indirect Indicator: Indirect

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.

Detailed

Description 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.
Data Engineering & AI Pipeline Design
  • 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.
Model Development & Orchestration
  • Develop, test, and refine AI prompts and orchestration workflows using frameworks like Lang Chain, Llama Index, 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.
Knowledge/Skills/Competencies Essential Skills
  • 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 (Num Py, Pandas, PyTorch, or Tensor Flow).
  • Experience with Cloud AI Services (Azure AI Studio, AWS Bedrock, or Google Vertex AI [Preferred]).
Desirable Skills
  • 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…
Position Requirements
10+ Years work experience
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