Senior AI Engineer, IT Solutions 1 1

Senior AI Engineer, IT Solutions 1 1

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
C

At a Glance

  • Tasks: Lead AI projects, translating business needs into innovative machine learning solutions.
  • Company: Join Celestica, a global leader in tech solutions with a customer-centric approach.
  • Benefits: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic work environment with excellent career advancement opportunities.
  • Why this job: Make a real impact by developing cutting-edge AI tools that drive innovation.
  • Qualifications: 11+ years in IT or Data Science, with strong AI/ML development skills.

The predicted salary is between 80000 - 100000 £ per year.

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.

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 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.

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 (NumPy, Pandas, PyTorch, or TensorFlow).
  • 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 required.

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.

This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.

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.

This policy applies to hiring, promotion, discharge, pay, fringe benefits, job training, classification, referral and other aspects of employment and also states that retaliation against a person who files a charge of discrimination, participates in a discrimination proceeding, or otherwise opposes an unlawful employment practice will not be tolerated. All information will be kept confidential according to EEO guidelines.

Location: This is a remote position, with travel as necessary.

Senior AI Engineer, IT Solutions 1 1 employer: Celestica

Celestica is an exceptional employer that fosters a dynamic work culture, encouraging innovation and collaboration among its diverse teams. With a strong focus on employee growth, the company offers numerous opportunities for professional development and advancement, particularly in the thriving Capital Equipment sector. Located in a vibrant area, Celestica provides a supportive environment where employees can thrive while contributing to impactful strategies and operations.

C

Contact Details:

Celestica Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior AI Engineer, IT Solutions 1 1

Tip Number 1

Network like a pro! Reach out to your connections in the AI and tech space. Attend meetups, webinars, or even online forums. You never know who might have the inside scoop on job openings or can refer you directly.

Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects, especially those that highlight your experience with Generative AI and machine learning. This will give potential employers a taste of what you can bring to the table.

Tip Number 3

Prepare for interviews by brushing up on common AI-related questions and scenarios. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.

We think you need these skills to ace Senior AI Engineer, IT Solutions 1 1

AI/ML Development
Generative AI
LLMs
Prompt Engineering
Vector Databases
Python
NumPy

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Senior AI Engineer role. Highlight your experience with AI/ML development and any relevant projects that showcase your skills in translating business challenges into technical solutions.

Showcase Your Technical Skills:Don’t hold back on detailing your technical expertise! Mention your proficiency in Python, experience with Generative AI, and familiarity with MLOps tools. We want to see how you can contribute to our Data & Analytics team.

Communicate Clearly:Remember, you’ll be liaising with both technical teams and business stakeholders. Use clear and concise language to explain complex AI concepts. This will demonstrate your ability to bridge the gap between tech and business.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!

How to prepare for a job interview at Celestica

Know Your AI Stuff

Make sure you brush up on the latest trends in AI and machine learning, especially around Generative AI and RAG patterns. Be ready to discuss specific projects you've worked on and how they relate to the job description.

Speak Their Language

Since you'll be liaising between technical teams and business stakeholders, practice explaining complex AI concepts in simple terms. Use examples from your past experiences to illustrate your points clearly.

Prepare for Technical Questions

Expect to dive deep into technical discussions. Review key concepts like model architectures, data ingestion pipelines, and MLOps best practices. Be prepared to solve problems on the spot or discuss how you would approach certain challenges.

Showcase Your Collaboration Skills

This role requires a lot of teamwork, so highlight your experience working with cross-functional teams. Share examples of how you've successfully collaborated with data engineers or business leaders to deliver AI solutions.