AI Engineer & Developer Path

London Academy of IT Limited; United Kingdom; On-site; GBP 40,000 - 60,000; Full time

Job summary

London Academy of IT Limited is offering a practical career path for aspiring AI Engineers & Developers, focusing on skills in Python, Machine Learning, and more. The program emphasizes real-world application development through comprehensive training and support.

Participants will engage in advanced programming, data science, and AI solution design, preparing for high-demand roles in various industries. This pathway not only builds fundamental coding skills but also delves into embedding AI technologies within modern business environments.

Qualifications

• Strong foundation in basic computing logic and problem-solving.
• Experience in programming and software design.
• Knowledge of machine learning and AI technologies.

Responsibilities

• Design and build AI-powered applications such as chatbots and intelligent assistants.
• Write clean and scalable Python code for AI algorithms.
• Integrate LLM APIs into company applications.
• Collaborate with teams to launch AI features.

Skills

Advanced Python programming

Object-oriented software design

API integrations

Data preparation

Feature scaling

Deep learning systems

Neural network topologies

Large Language Model (LLM) prompts

Retrieval-Augmented Generation (RAG)

Multi-agent systems

Job description

Follow a practical AI Engineer & Developer career path with instructor-led training in Python, Machine Learning, Deep Learning, Generative AI, LLMs, RAG, APIs and AI application development.

An AI Engineer & Developer designs, builds, integrates, and deploys Artificial Intelligence solutions that can analyse data, automate tasks, generate content, answer questions, make predictions, and support intelligent decision-making.

The London Academy of IT AI Engineer & Developer Career Path is designed to help learners build practical AI development skills using modern technologies including Python, Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), APIs, Vector Databases, and AI Frameworks.

This pathway focuses on both the engineering and application-development sides of Artificial Intelligence. Learners progress from programming and data foundations into building real-world AI-powered applications such as chatbots, intelligent assistants, document analysis systems, recommendation engines, AI automation tools, and agentic AI solutions.

As organisations increasingly adopt AI technologies, there is growing demand for professionals who can move beyond simply using AI tools and instead build, customise, integrate, and deploy AI solutions that solve real business problems. AI engineering skills are becoming increasingly valuable across industries including technology, finance, healthcare, education, consulting, retail, government, and enterprise automation.

This career path is suitable for aspiring AI Engineers, Software Developers, Data Professionals, Technical Consultants, Automation Specialists, and learners who want to build modern AI applications using todays rapidly evolving technologies.

Recommended Learning Pathway

Complete these milestone training steps sequentially to achieve full proficiency:

This career path is designed to be accessible to programming enthusiasts, backend developers, and tech career changers. While no previous background in artificial intelligence is required to start, having a strong foundation in basic computing logic, step-by-step problem-solving, and clean script writing will help you progress through the advanced modules smoothly.

To establish professional-grade technical authority as an AI Engineer, you should develop comprehensive skills in:

• Advanced Python programming, object-oriented software design, and API integrations
• Data preparation, feature scaling, and feature optimisation libraries like Pandas and NumPy
• Supervised and unsupervised predictive model structures using Scikit-Learn algorithms
• Deep learning systems, neural network topologies, and computer vision models using TensorFlow
• Large Language Model (LLM) prompts, engineering strategies, and fine-tuning APIs via OpenAI, Claude, and Hugging Face
• Retrieval-Augmented Generation (RAG) implementation and vector database logic for custom enterprise knowledge bases
• Agentic AI frameworks, automated tool calling, and multi-agent systems designed to perform autonomous tasks

Day-to-Day Responsibilities

AI Engineers combine software engineering principles with data science capabilities to design, test, build, and maintain smart software systems that automate manual tasks and power conversational platforms.

• Writing clean, robust, and scalable Python code to run AI algorithms across web and software environments
• Integrating commercial LLM APIs and open-source models into custom company applications
• Designing and building RAG data pipelines to connect internal company documentation safely to conversational interfaces
• Training, testing, and optimising predictive machine learning models to analyse user actions or business trends
• Developing autonomous AI agents capable of performing multi-step workflows, tool calls, and background automation
• Collaborating with software developers, product management teams, and infrastructure engineers to roll out AI features securely
• Monitoring model responses to prevent hallucinations, secure data inputs, and ensure your system meets quality standard metrics

Market Opportunities & Career Landscape

The marketplace for artificial intelligence development is experiencing rapid, unprecedented growth. Industries ranging from finance, customer experience networks, healthcare systems, retail automation platforms, and legal tech consulting firms are actively restructuring operations around generative workflows, custom language models, and autonomous software agents.

Because these technologies are evolving so quickly, organisations face an immense shortage of engineers who know how to deploy and manage AI systems rather than just use ready-made chatbots. This significant talent gap creates excellent, high-value career opportunities for professionals who can bridge the gap between classic backend engineering and smart model deployment workflows.

This path provides an ideal blueprint for software engineers looking to move into high-demand AI development, data analysts transitioning into model automation roles, and technical entrepreneurs looking to prototype and launch smart software products.

At London Academy of IT, we provide instructor-led online and in-person IT training in Data Analytics, SQL, Python, Power BI, and more. Our cutting-edge courses are designed to boost performance and enhance employability, providing the competitive edge employers look for.

Our Contacts

London Academy of IT

64 Broadway

Stratford

London E15 1NT

United Kingdom