At a Glance
- Tasks: Design and deliver enterprise-scale AI solutions that make a real business impact.
- Company: Join Wipro, a leader in innovative AI and ML solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a dynamic environment focused on innovation.
- Why this job: Be at the forefront of AI technology and drive transformative change in businesses.
- Qualifications: Experience in AI/ML engineering and cloud platforms is essential.
The predicted salary is between 80000 - 100000 £ per year.
Wipro brings a Principal AI/ML Solutions Architect to partner with your organisation in designing and delivering enterprise-scale AI, MLOps, and Generative AI platforms. This role combines deep technical expertise with strategic advisory capability, ensuring your AI investments move beyond experimentation into production-grade, scalable, and business-impacting solutions.
What This Role Delivers
- AI Strategy to Execution
- Define AI/ML and GenAI roadmaps aligned to business priorities
- Translate use cases into scalable, production-ready architectures
- Provide C-suite advisory on AI adoption, governance, and operating models
- Enterprise AI Platform Engineering
- Design and implement cloud-MLOps platforms across AWS, Azure, and GCP
- Enable end-to-end ML lifecycle: data-training-deployment-monitoring
- Build secure, automated CI/CD pipelines for model deployment at scale
- Generative AI & LLM Enablement
- Deploy GenAI solutions including RAG architectures and enterprise knowledge systems
- Build agentic AI workflows for automation and decision intelligence
- Ensure responsible AI, explainability, and governance by design
- Data & Real-Time Intelligence
- Implement real-time and batch data pipelines (Kafka, Spark, Airflow)
- Enable advanced feature engineering and predictive analytics
- Support streaming inference and operational AI use cases
- Scaled Delivery & Transformation
- Lead multi-disciplinary AI teams across engineering, data science, and DevOps
- Deliver production-grade AI solutions in complex, regulated environments
- Accelerate outcomes using pre-built frameworks and accelerators
Core Capabilities
- AI/ML Engineering: TensorFlow, PyTorch, XGBoost, transformer architectures
- MLOps & LLMOps: MLFlow, Kubeflow, SageMaker, KServe, vector DBs
- Cloud & Platform Engineering: AWS, Azure, GCP, Kubernetes, Terraform
- Data Platforms: Spark, Kafka, Snowflake, Airflow
- Responsible AI: Explainability (SHAP), model governance frameworks
Business Impact
- Accelerated AI adoption from PoC to production
- Reduced time-to-market for ML use cases
- Improved model reliability, governance, and compliance
- Enabled scalable GenAI capabilities across the enterprise
- Delivered measurable ROI through AI-driven decisioning
Ideal Engagement Scenarios
- Enterprise AI platform modernisation
- Scaling MLOps / LLMOps capabilities
- Implementing GenAI-driven knowledge and automation platforms
- Driving AI-led transformation across business units
AI Solution architect in London employer: Energy Jobline ZR
Wipro is an exceptional employer for AI Solution Architects, offering a dynamic work environment in London that fosters innovation and collaboration. With a strong focus on employee growth, Wipro provides access to cutting-edge technology and training opportunities, ensuring that team members can thrive in their careers while contributing to impactful AI solutions. The company's commitment to responsible AI practices and its diverse, inclusive culture make it a rewarding place to work for those passionate about shaping the future of technology.
StudySmarter Expert Advice🤫
We think this is how you could land AI Solution architect in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI space. Attend meetups, webinars, or even local tech events. The more people you know, the better your chances of landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, whether they're personal or professional. 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 practising common questions related to AI architecture and MLOps. We recommend doing mock interviews with friends or using online platforms to get comfortable with your responses.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Solution architect in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of AI Solution Architect. Highlight your experience with AI/ML, cloud platforms, and any relevant projects that showcase your skills in designing scalable solutions.
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. Be specific about your achievements and how they relate to the job.
Showcase Your Technical Skills:Don’t hold back on your technical expertise! Mention your experience with tools like TensorFlow, AWS, or MLOps frameworks. We want to see how you can contribute to our AI strategy and execution.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your AI Inside Out
Make sure you brush up on your knowledge of AI/ML technologies, especially TensorFlow, PyTorch, and MLOps tools like MLFlow and Kubeflow. Be ready to discuss how you've applied these in real-world scenarios, as this will show your deep technical expertise.
✨Showcase Your Strategic Thinking
Prepare to talk about how you would define AI roadmaps aligned with business priorities. Think of examples where you've translated complex use cases into scalable architectures, and be ready to explain your thought process behind those decisions.
✨Demonstrate Leadership Skills
Since this role involves leading multi-disciplinary teams, think of instances where you've successfully managed diverse groups. Highlight your experience in delivering production-grade solutions in regulated environments, as this will resonate well with the interviewers.
✨Emphasise Responsible AI Practices
Be prepared to discuss how you ensure responsible AI and model governance. Familiarise yourself with concepts like explainability and compliance, and share any frameworks or practices you've implemented to uphold these standards in your previous roles.
