At a Glance
- Tasks: Design and build secure, scalable cloud infrastructure and AI applications using cutting-edge technologies.
- Company: Join a forward-thinking tech company focused on Cloud & AI solutions.
- Benefits: Enjoy competitive salary, health benefits, hybrid work, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real impact in the exciting world of cloud and AI technology.
- Qualifications: Experience with AWS, DevSecOps practices, and strong communication skills required.
The predicted salary is between 63000 - 77000 £ per year.
Location: London, United Kingdom (Hybrid – 50% work from client office)
Employment Type: Full-time
Security Clearance: Must hold or be eligible to obtain UK Security Check (SC) Clearance
About the Role
As a Cloud Architect (DevSecOps & LLMOps Engineer), you will make an impact by designing, building, securing, and operating scalable cloud infrastructure and enterprise Generative AI applications that drive automation, observability, and modern LLMOps practices. You will be a valued member of our Cloud & AI Engineering team and work collaboratively with architects, developers, security teams, and business stakeholders to deliver secure, resilient, scalable, and cost-effective cloud and AI solutions using AWS Bedrock and related technologies.
In this role, you will:
- Design, implement, and support secure, scalable AWS infrastructure and AI platforms using Terraform, GitHub Actions, Ansible, ECS/Fargate, and AWS native services.
- Build and operationalise enterprise GenAI solutions using Amazon Bedrock, LLMs, RAG pipelines, vector databases, embeddings, chunking strategies, workflow orchestration (DAG/agentic), and AI observability.
- Develop and maintain CI/CD pipelines, Infrastructure as Code, API integrations, cloud security, IAM governance, monitoring, logging, and production BAU support.
- Configure and manage application observability using Datadog (or equivalent), including dashboards, APM, log analytics, infrastructure monitoring, alerting, and operational health reporting.
- Collaborate with architects, developers, security teams, and business stakeholders to deliver secure, resilient, scalable, and cost-effective cloud and AI solutions.
What You Need to Have to Be Considered
- Strong hands-on experience with AWS services including Amazon Bedrock, ECS/Fargate, Lambda, EC2, API Gateway, VPC, ALB, IAM, CloudWatch, S3, EFS, DynamoDB, and Neptune, alongside Infrastructure as Code using Terraform.
- Strong experience with DevSecOps practices including GitHub Actions, Ansible, Docker, CI/CD automation, security scanning, secrets management, monitoring, logging, and production support.
- Good understanding of LLMOps concepts including LLMs, RAG, embeddings, chunking, vectorisation, vector databases, semantic search, prompt engineering, workflow orchestration (DAG/LangGraph), AI guardrails, and model evaluation.
- Strong experience with API Management platforms such as Amazon API Gateway, Kong, Apigee, or equivalent — with the ability to design, configure, and implement API proxy workflows, authentication, routing, policies, transformations, and API integrations.
- Strong experience with Datadog (or equivalent monitoring platform) for dashboard creation, application monitoring, alert configuration, APM, log analytics, and performance troubleshooting.
- Excellent communication, stakeholder management, and client-facing skills.
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
- Must currently reside in the United Kingdom.
- Must be available to start within 4 weeks of receiving an offer.
- Must hold or be eligible to obtain UK Security Check (SC) Clearance.
These Will Help You Stand Out
- Experience with Kubernetes/EKS, Docker, ServiceNow, Jira, GitHub Runners, CloudFormation, Route 53, WAF, EventBridge, Step Functions, and serverless architectures.
- Hands-on experience with Python development for automation, API integrations, scripting, and cloud-native application development.
- Experience building AI data pipelines, including document ingestion, preprocessing, metadata enrichment, chunking, embedding generation, vector indexing, and retrieval workflows.
- Familiarity with AI prompt development, prompt tuning, prompt templates, and prompt evaluation techniques.
- Exposure to vector databases, OpenSearch, LangChain/LangGraph, knowledge graphs (Neptune), cloud networking, security best practices, cost optimisation, and enterprise production support.
Additional eligibility requirements:
- Candidates must hold or be eligible to obtain UK Security Check (SC) Clearance.
- Candidates must be available to start within 4 weeks of receiving an offer.
Cloud Architect in London employer: Cognizant
Cognizant is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for professionals seeking to excel in their careers. With a strong emphasis on employee growth and development, you will have access to mentorship opportunities and the chance to lead transformative projects in a dynamic environment. Located in a vibrant area, Cognizant offers unique advantages such as a diverse team and a commitment to work-life balance, ensuring that your contributions are both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Cloud Architect in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Cognizant or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Cognizant.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Cognizant.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Cognizant that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Cloud Architect in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Cognizant.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Cognizant and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Cognizant
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Cognizant uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
