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.

• 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

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

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+.

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

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.

Salary: £30k – £40k
What They Do:
Assists in developing and training machine learning models, cleans and processes data, and supports senior AI engineers or researchers.

Skills Needed:

• Basic understanding of ML algorithms and neural networks
• Programming skills in Python, R, or Julia
• Experience with ML libraries (TensorFlow, PyTorch, scikit-learn)
• Data preprocessing and visualisation
• Knowledge of cloud platforms (AWS, GCP, Azure)

Salary: £40k – £55k
What They Do:
Designs and deploys machine learning models, integrates them into applications, and collaborates with data scientists and software engineers.

Skills Needed:

• Strong foundation in supervised and unsupervised learning
• Experience building and deploying models at scale
• Familiarity with MLOps and CI/CD pipelines for ML
• Understanding of APIs and microservices
• Optimisation and performance tuning of models

Salary: £55k – £75k
What They Do:
Leads AI model development projects, evaluates cutting-edge approaches (e.g., transformers, LLMs), and mentors junior team members.

Skills Needed:

• Deep learning architectures and generative AI models (GANs, diffusion models, LLMs)
• Data pipeline design and distributed computing
• AI ethics and model explainability
• Advanced programming and systems design
• Collaboration with product teams to align AI initiatives

Salary: £75k – £90k
What They Do:
Designs AI systems that integrate across business units, manages AI product lifecycles, and ensures solutions meet business goals.

Skills Needed:

• AI system architecture and integration
• Product management for AI-driven solutions
• Stakeholder communication and requirements gathering
• Vendor and technology partner management
• Security and compliance in AI solutions

Salary: £90k – £120k
What They Do:
Defines the AI strategy, manages AI teams, and drives innovation across the business. Aligns AI initiatives with organisational goals.

Skills Needed:

• Department-level leadership and strategic planning
• Experience scaling AI teams and infrastructure
• Budget and roadmap ownership
• Advanced understanding of AI regulations and ethics
• Executive-level communication and influencing skills

Salary: £130k – £160k+
What They Do:
Owns the company’s AI vision and strategy, ensures AI-driven innovation across products and services, and reports to the board.

Skills Needed:

• Executive-level leadership and vision
• Enterprise-wide AI strategy and investment planning
• Driving AI/GenAI adoption and transformation
• Global partnerships and vendor management
• Board-level advocacy of AI as a growth driver