Technical Architect

HCL Technologies; City of Westminster; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading technology company in the United Kingdom is seeking a GEN AI Architect to shape the design and deployment of advanced Gen AI systems. The ideal candidate has a strong background in AI system development, programming skills in Python, and experience with large language models. This role emphasizes collaboration with teams to deliver innovative AI solutions while following ethical practices.

Qualifications

• A bachelor's or master's degree in computer science, Artificial Intelligence, or related field.
• Experience with large language models (LLMs) and prompt engineering.
• Strong programming skills in languages such as Python, R, or Java.
• Understanding of cloud computing platforms (AWS, Azure, Google Cloud).
• Knowledge of AI libraries and frameworks.

Responsibilities

• Design and develop the architecture for Gen AI systems.
• Develop advanced AI algorithms and models.
• Identify and design methods for data integration.
• Train AI models using various learning techniques.
• Collaborate with teams for system integration.

Skills

Experience with large language models (LLMs)

Strong programming skills in Python

Experience in AI systems development

Problem-solving skills

Familiarity with TensorFlow

Knowledge of cloud computing platforms

Education

Bachelor's or Master's in Computer Science or AI

Tools

TensorFlow

PyTorch

Keras

Job description

GEN AI Architect Job Description

Job Role Overview: As a GEN AI Architect, you will play a pivotal role in shaping the design, development, and deployment of advanced Gen AI systems within our organization. This position demands a visionary problem‑solver who combines technical expertise with a passion for innovation. You will work collaboratively with multidisciplinary teams to create scalable, efficient, and ethical AI solutions that drive business value and push the boundaries of artificial intelligence technology.

Key Responsibilities

• AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the system's scalability, flexibility, and efficiency to handle large algorithms.
• Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy.
• Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training.
• Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine‑tune models based on feedback and data insights.
• Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency.
• System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications, ensuring seamless communication and compatibility between AI components and other software modules.
• Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage.
• Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities.
• Teamwork and Communication: Collaborate with cross‑functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non‑technical audiences.

Mandatory Qualifications/Skills

• A bachelor's or master's degree or equivalent in computer science, Artificial Intelligence, or related field.
• Experience with large language models (LLMs) and prompt engineering.
• Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks.
• Strong programming skills in languages such as Python, R, or Java.
• Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras.
• Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
• Solid understanding of AI concepts, algorithms, and methodologies.
• Knowledge of designing large‑scale AI solutions, data integration, cleansing, and transformation techniques.
• Excellent problem‑solving and analytical skills, with the ability to think creatively and provide innovative solutions.