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- Tasks: Lead the design and implementation of AI-driven products across various industries.
- Company: Join Infosys, a global leader in digital services and consulting.
- Benefits: Competitive salary, diverse work culture, and opportunities for continuous learning.
- Why this job: Shape the future of AI technology and make a real impact in multiple domains.
- Qualifications: Strong foundation in AI/ML, excellent communication, and collaborative skills.
- Other info: Dynamic environment with endless opportunities for career growth and innovation.
The predicted salary is between 43200 - 72000 £ per year.
The AI Architect will lead the design and implementation of AI-driven product capabilities across multiple domains like Aero, Manufacturing, Retail, Finance etc using both Traditional & Generative AI + Machine Learning. The role involves defining architecture, guiding development, and enabling innovation across AI/ML, LLM, RAG, and Agentic AI use cases. The ideal candidate combines strong technical depth with product mindset, collaboration, and leadership. The candidate should have technical consulting capabilities, solutioning acumen, and domain knowledge on any of the industries where GEN AI is applied. The candidate should be able to conduct value stream workshops in discovering the AI implementation scope and able to create architecture and detailed solutions. Candidate should have excellent communication skills.
Key Responsibilities:
- Architect and deliver scalable GenAI solutions across data, model, and application layers.
- Define reference architectures, reusable patterns, and best practices for AI integration into products.
- Design and operationalize LLM, RAG, Copilot, and Agentic AI workflows.
- Familiarity with ML and able to integrate AI/ML solutions.
- Establish MLOps and GenAIOps pipelines for model lifecycle management, monitoring, and governance.
- Collaborate with product, data, and engineering teams to translate business needs into AI-enabled features.
- Lead PoCs and innovation initiatives to evaluate emerging frameworks and technologies.
- Mentor teams on AI engineering, prompt design, and scalable deployment practices.
- Support pre-sales and customer discussions to define solution approaches and architecture options.
- Familiarity of a Product development Value chain in a domain.
Skills & Experience:
- Strong foundation in NLP, and LLM-based architectures.
- Familiarity with machine learning, deep learning (strong knowledge is an added advantage).
- Hands-on expertise with Python, TensorFlow, PyTorch, LangChain, LangGraph/CrewAI/AutoGen, Hugging Face, and MLflow.
- Experience with cloud AI ecosystems — AWS (SageMaker, Bedrock), Azure (AI Studio, OpenAI), or GCP (Vertex AI).
- Experience in Foundation models, Codex tool plugins, New Coding tools (Cursor, Devin).
- Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, MILVUS) and RAG pipelines.
- Familiarity with containerization (Docker, Kubernetes) and MLOps workflows.
- Exposure to prompt engineering, fine-tuning, evaluation, and responsible AI practices.
- Understanding of data engineering, model observability, and AI governance.
Soft Skills:
- Strong analytical, problem-solving, and communication abilities.
- Collaborative mindset with ability to work across product, engineering, and data teams.
- Thought leadership in driving AI adoption, innovation, and best practices.
- Experience supporting AI CoE initiatives and customer engagements.
AI Architect | London employer: ITL UK
Contact Detail:
ITL UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Architect | London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI space. Attend meetups, webinars, or industry events. You never know who might be looking for an AI Architect just like you!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving NLP and LLM architectures. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Practice your pitch! Be ready to explain your experience and how it aligns with the role. Highlight your technical depth and product mindset, and don’t forget to mention your collaborative spirit!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to reflect your understanding of AI-driven solutions and how you can contribute to our innovative projects.
We think you need these skills to ace AI Architect | London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Architect role. Highlight your expertise in NLP, LLM architectures, and any relevant projects you've worked on. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our needs. Don't forget to mention specific technologies or methodologies you've used that relate to the job description.
Showcase Your Projects: If you've led any innovative AI projects or PoCs, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they demonstrate your ability to collaborate across teams and drive AI adoption.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at ITL UK
✨Know Your AI Stuff
Make sure you brush up on your knowledge of NLP, LLM architectures, and the latest in machine learning. Be ready to discuss specific projects you've worked on that showcase your expertise with tools like TensorFlow or PyTorch.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex problems in AI architecture. Think about times when you led a project or innovated a solution, especially in areas like MLOps or GenAIOps.
✨Communicate Clearly
Since communication is key for this role, practice explaining technical concepts in simple terms. You might be asked to describe your approach to integrating AI solutions, so clarity will help you stand out.
✨Collaborate and Lead
Be ready to discuss your experience working with cross-functional teams. Highlight any leadership roles you've taken on, especially in guiding development or conducting workshops to define AI implementation scopes.
