AI & GenAI jobs and careers

Artificial Intelligence (AI) and Generative AI are transforming how companies operate, make decisions, and interact with customers. By automating processes, generating content, and uncovering patterns in large data sets, these technologies offer powerful tools to drive innovation and business performance. From enhancing customer experiences to improving operational efficiency, AI is at the forefront of modern digital transformation.

Why consider a career in AI & Generative AI?

As AI and Generative AI become increasingly embedded across industries and various companies start implementing AI into their businesses, demand is growing for professionals who can build, implement, and manage these systems.

A career in AI offers opportunities to work on cutting-edge technologies and projects with real-world impact. Whether you’re developing intelligent systems or fine-tuning machine learning models, the field promises continual learning, career growth, and the chance to shape the future.

What are typical AI & Generative AI job titles?

  • AI Engineer
  • Machine Learning Engineer
  • Deep Learning Engineer
  • NLP (Natural Language Processing) Engineer
  • AI Research Scientist
  • Data Scientist
  • Generative AI Engineer
  • AI Product Manager
  • Computer Vision Engineer
  • Robotics Engineer
  • AI Solutions Architect
  • Applied AI Specialist
  • MLOps Engineer
  • AI Ethics Specialist
  • Prompt Engineer
  • Large Language Model (LLM) Engineer
  • AI/ML Consultant

AI & Generative AI: Career Progression Example

  • Junior AI Engineer
  • AI Engineer
  • Senior AI Engineer
  • Lead AI/ML Engineer
  • Head of AI
  • Director of AI / Chief AI Officer
  • AI/ML Architect

AI & Generative AI Salary Benchmarks

At an entry level, Junior/Graduate PPC Consultants on average will be earning between £20-30k. At mid-level, you’d be looking to earn £30k-50k and seniors would be looking to earn £50k+.

AI & Generative AI: Is It Right for Me? The Skills It Takes…

The skillset required for a successful AI/GenAI career typically spans across four areas: technical skills, applied AI skills, and soft/strategic skills.

Technical Skills: Programming (Python, R, Java, C++) | Machine Learning and Deep Learning | Data Engineering and Data Preprocessing | Neural Networks (CNNs, RNNs, Transformers) | APIs and AI Model Integration | Working with Cloud Platforms (AWS, Azure, GCP) | Experience with Frameworks (TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face Transformers) | SQL and NoSQL Databases | Model Deployment, Versioning, and MLOps Practices (MLflow, DVC, Kubeflow, SageMaker)

Applied AI Skills: Natural Language Processing (NLP) | Computer Vision | Generative AI Tools (ChatGPT, Claude, Gemini, Copilot, DALL·E, Midjourney, Runway ML, Sora) | Fine-Tuning and Prompt Engineering for LLMs | Responsible and Ethical AI Principles | Knowledge of Large-Scale Data Architectures | Experience with Vector Databases and Embeddings (FAISS, Pinecone, Weaviate, Chroma) | Understanding of Reinforcement Learning and Generative Adversarial Networks (GANs) | AI Model Evaluation and Interpretability (SHAP, LIME, Captum)

AI Tools and Technologies: Hugging Face Hub | OpenAI API | LangChain | LlamaIndex | Weights & Biases | Azure OpenAI Studio | Google Vertex AI | IBM Watson | AutoML Platforms (DataRobot, H2O.ai, Google AutoML) | Data Labelling Tools (Label Studio, Prodigy) | Speech and Audio AI (Whisper, AssemblyAI) | Computer Vision Platforms (Roboflow, OpenCV, YOLO)

Soft and Strategic Skills: Analytical Thinking and Problem-Solving | Communicating Complex Ideas to Non-Technical Stakeholders | Curiosity and Adaptability | Collaboration in Cross-Functional Teams | Strategic and Product-Oriented Thinking | Ability to Assess AI Feasibility and Business Impact

What Qualifications Do You Need for a Career in AI & Generative AI?

Typically, a Bachelor’s degree (or similar) in Computer Science, Mathematics, Engineering, Physics, Statistics, or a related STEM subject is required. Many roles also benefit from (or require) postgraduate qualifications in Artificial Intelligence, Machine Learning, or Data Science. Certifications and practical experience with AI platforms and tools are highly valuable.

Our Data, Insight & Analytics recruitment team

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    Data, Insight & Analytics

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    Tegan Fenn

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