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For Companies At a Glance
- 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, bonuses, and opportunities for continuous learning.
- Why this job: Shape the future of AI technology and make a real impact in diverse sectors.
- 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 48000 - 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 in 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 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 with 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 with 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: Infosys
Contact Detail:
Infosys 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 have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving GenAI, LLM, or any cool AI workflows you've worked on. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, TensorFlow, and any relevant AI frameworks. Practice explaining complex concepts in simple terms – communication is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight your experience with AI/ML 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 GenAI, LLM, 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. Be sure to mention specific technologies or methodologies you've used that relate to the job description.
Showcase Your Communication Skills: Since excellent communication is key for this role, make sure your application materials are clear and concise. We want to see how you articulate complex ideas, so don’t shy away from demonstrating your thought process in your writing.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at StudySmarter!
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 GenAI, LLM, and MLOps. Brush up on your Python, TensorFlow, and cloud ecosystems like AWS or Azure. Being able to discuss these confidently will show that you’re not just familiar but truly knowledgeable.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems using AI solutions. Think about how you’ve defined architectures or led innovation initiatives in previous roles. This will demonstrate your analytical abilities and how you can apply them in real-world scenarios.
✨Communicate Clearly and Effectively
Since excellent communication skills are a must, practice explaining technical concepts in simple terms. You might be asked to lead discussions or workshops, so being able to articulate your thoughts clearly will set you apart from other candidates.
✨Collaborate and Connect
Highlight your experience working with cross-functional teams. Discuss how you’ve collaborated with product, data, and engineering teams to translate business needs into AI features. This shows that you’re not just a tech whiz but also a team player who can drive projects forward.
