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- Tasks: Lead the design and implementation of AI-driven product capabilities across various industries.
- Company: Join Infosys, a global leader in digital services and consulting.
- Benefits: Competitive salary with bonuses, inclusive culture, and opportunities for continuous learning.
- Why this job: Shape the future of AI technology and make a real impact across multiple domains.
- Qualifications: Strong foundation in NLP, LLM architectures, and hands-on experience with AI tools.
- Other info: Collaborative environment with excellent career growth and innovation opportunities.
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. 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 Gen AI 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 ML Ops and Gen AI Ops 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.
Senior Technology Architect in London employer: Infosys
Contact Detail:
Infosys Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Technology Architect in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repository showcasing your projects related to AI and ML. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to AI architecture. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior Technology Architect in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Technology Architect role. Highlight your expertise in AI, ML, and relevant technologies like Python and TensorFlow to catch our eye!
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 any leadership or collaborative experiences you've had.
Showcase Your Projects: If you've worked on any AI-driven projects or innovations, make sure to include them in your application. We love seeing real-world applications of your skills, especially in areas like LLM and RAG.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right team!
How to prepare for a job interview at Infosys
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Gen AI, LLM, and RAG. Brush up on your knowledge of Python, TensorFlow, and cloud ecosystems like AWS or Azure. Being able to discuss these topics confidently will show that you’re the right fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems using AI solutions. Think about how you’ve led projects or workshops that align with the responsibilities listed, such as defining architectures or mentoring teams. Real-world examples will make your experience stand out.
✨Communicate Clearly and Effectively
Since excellent communication skills are a must, practice articulating your thoughts clearly. Be ready to explain technical concepts in simple terms, especially when discussing AI workflows or ML Ops. This will demonstrate your ability to collaborate across teams, which is crucial for this role.
✨Be Ready for Scenario-Based Questions
Expect questions that assess your approach to real-world scenarios, like leading PoCs or integrating AI into products. Prepare by thinking through how you would handle various challenges in AI implementation. This will help you showcase your strategic thinking and solutioning acumen.
