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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 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 AI/ML, experience with Python, and excellent communication skills.
- Other info: Collaborative environment with opportunities for innovation and career growth.
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 candidate should have strong technical depth, product mindset, collaboration and leadership, with technical consulting capabilities, solutioning acumen, and domain knowledge in industries where GenAI is applied. The candidate should be able to conduct value stream workshops to discover the AI implementation scope and create architecture and detailed solutions. Excellent communication skills are required.
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 the ability 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 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: Infosys Limited
Contact Detail:
Infosys Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Architect | London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving GenAI and LLMs. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to AI architecture and workflows. Practice explaining complex concepts in simple terms, as communication is key in this role.
✨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 about their job search!
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 mission at StudySmarter. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Mention specific tools and technologies you’ve used, like Python, TensorFlow, or cloud ecosystems. We’re looking for someone who can hit the ground running, so let us know what you bring to the table.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our awesome team at StudySmarter!
How to prepare for a job interview at Infosys Limited
✨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 any relevant frameworks. Being able to discuss these in detail will show your technical depth and product mindset.
✨Showcase Your Collaboration Skills
Since the role involves working with various teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your experience in leading workshops or mentoring others, as this demonstrates your leadership and communication abilities.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems or design solutions on the spot. Practice articulating your thought process clearly, especially when discussing AI workflows or architecture design. This will help you showcase your solutioning acumen.
✨Demonstrate Your Passion for AI Innovation
Talk about any personal projects or initiatives you've undertaken related to AI. Whether it’s a PoC you led or a new technology you explored, showing your enthusiasm for driving AI adoption and innovation can set you apart from other candidates.
