At a Glance
- Tasks: Design and build an AI platform for automating software delivery lifecycle.
- Company: Join a leading tech firm in London with a hybrid work culture.
- Benefits: Enjoy competitive salary, health perks, and opportunities for professional growth.
- Other info: Collaborate with top talent in a dynamic environment focused on career advancement.
- Why this job: Be at the forefront of AI innovation and shape the future of software development.
- Qualifications: Strong experience in software architecture and AI engineering required.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for an experienced AI Platform Architect to design, architect, build, and operationalise an enterprise Agentic AI Harness that enables end-to-end SDLC automation across .NET and Azure environments. The successful candidate will define the architecture, standards, patterns, and operating model for an agent-based engineering platform scaffolding or harness using GitHub Copilot Agents and frameworks such as Microsoft Agent Framework, ADK, LangGraph, LangChain, and LangFuse. This harness will automate and assist key SDLC activities, including requirements generation, specification creation, story breakdown, architecture and design decision capture, task planning, test generation, code creation, test execution, infrastructure-as-code generation, and CI/CD pipeline creation. The target outcome of the harness will be production-ready .NET applications deployable into Azure cloud environments. In addition to designing and implementing the platform, the role will provide architectural leadership and guidance to architects and engineering teams, helping establish Agentic Software Delivery practices across the organisation. This role is ideal for someone with strong software architecture experience, practical AI engineering skills, and a deep understanding of modern DevOps, cloud-native architecture, platform engineering, and enterprise-grade application delivery.
Tech Skills Required
- AI and Agentic Engineering
- Experience designing and building AI agents, multi-agent workflows, or agentic orchestration systems
- Practical knowledge of frameworks such as Microsoft Agent Framework, ADK, LangGraph, LangChain and LangFuse
- Prompt engineering, tool calling, structured outputs, agent memory, planning, routing, and evaluation patterns
- Experience integrating LLMs with enterprise systems, repositories, APIs, and development workflows
- Understanding of AI observability, tracing, evaluation, guardrails, and feedback loops
- Experience defining architecture patterns and governance for enterprise AI platforms
- SDLC Automation and Developer Productivity
- Experience using AI coding tools such as GitHub Copilot, Claude Code and Cursor
- Ability to design automated workflows for:
- Requirements analysis
- Specification generation
- User story creation
- Architecture and design decision records
- Task breakdown
- Test case generation
- Test plan creation
- Code generation
- Test execution
- Documentation generation
- Experience defining engineering standards, reusable templates, and software delivery patterns
- Software Architecture and Engineering
- Strong experience with .NET / C#
- Experience designing APIs, services, backend systems, and cloud-native applications
- Good understanding of software architecture, clean code principles, design patterns, secure coding practices, and Test-Driven Development (TDD) methodologies
- Experience with unit testing, integration testing, functional testing, and automated test execution
- Familiarity with test frameworks and automated testing tools used within the .NET ecosystem
- Experience producing architecture artefacts including reference architectures, architecture decision records, and implementation blueprints
- Cloud and Platform Architecture
- Strong experience with Microsoft Azure
- Experience designing cloud-native platforms and developer enablement capabilities
- Understanding of Infrastructure-as-Code, CI/CD pipelines, platform engineering, and cloud governance
- Experience designing secure, scalable, and resilient enterprise solutions
What the Role Will Do
The AI Platform Architect will be responsible for defining, designing, and implementing an Agentic SDLC platform capable of supporting the full software delivery lifecycle.
Key Responsibilities
- Define the target-state architecture for an Agentic Software Delivery platform
- Design and build an AI Agentic Harness that orchestrates multiple AI agents across the SDLC
- Create reference architectures, reusable patterns, standards, and implementation blueprints for Agentic Engineering
- Use frameworks such as Microsoft Agent Framework, ADK, LangGraph, LangChain, and LangFuse to create agent workflows
- Integrate the harness with development tools such as GitHub Copilot, Claude Code, Cursor, GitHub, Azure DevOps, and CI/CD platforms
- Establish architectural guardrails, governance controls, and quality standards for AI-generated software delivery
- Build agents that can generate:
- Business and technical specifications
- Epics, features, and user stories
- Acceptance criteria
- Design decisions and architecture decision records
- Engineering tasks and implementation plans
- Test cases and test plans
- .NET application code
- Infrastructure-as-Code templates
- CI/CD pipeline templates
- Deployment documentation
- Execute the harness to generate working .NET / C# code
- Build validation loops to review generated outputs for correctness, security, quality, and maintainability
- Create test automation capabilities that generate and execute tests against produced code
- Implement mechanisms for code review, quality checks, static analysis, and automated feedback
- Ensure generated applications are deployable into Azure environments
- Create reusable patterns, templates, prompts, workflows, and agent configurations
- Implement observability and traceability for agent decisions, tool usage, prompts, responses, and generated artefacts
- Work with enterprise architects, solution architects, engineers, product owners, and platform teams to align the harness with enterprise engineering standards
- Train and mentor architects and development teams on Agentic Software Delivery approaches and AI-assisted engineering practices
- Contribute to security, compliance, governance, and responsible AI controls around AI-generated software delivery
- Continuously improve the platform based on output quality, developer feedback, and delivery outcomes
Nice to Have Skills
- Experience with Semantic Kernel, Azure AI Foundry, Azure OpenAI, or OpenAI APIs
- Experience with Model Context Protocol (MCP) tools and agent tool integration
- Experience creating reusable software factory, internal developer platform, or platform engineering capabilities
- Familiarity with DevSecOps, secure SDLC, and automated security testing
- Experience building RAG-based systems or integrating AI agents with enterprise knowledge bases
- Knowledge of enterprise data privacy, Responsible AI, and AI governance controls
- Experience working in Agile delivery environments
- Ability to create technical documentation, reference architectures, architecture standards, and engineering playbooks
- Experience coaching architects and engineering teams on modern software delivery practices and AI adoption
Senior AI Platform Architect – Agentic SDLC Automation in London employer: CSI GLOBAL LTD
Join a forward-thinking company in London that champions innovation and collaboration, offering a hybrid work model that promotes work-life balance. As a Senior AI Platform Architect, you'll thrive in a culture that values continuous learning and professional growth, with opportunities to lead architectural initiatives and mentor teams in cutting-edge AI technologies. Enjoy competitive benefits and the chance to make a significant impact on enterprise software delivery practices while working in a vibrant city known for its tech advancements.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Platform Architect – Agentic SDLC Automation 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 CSI GLOBAL LTD 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
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✨Tap into Online Developer Communities
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We think you need these skills to ace Senior AI Platform Architect – Agentic SDLC Automation 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 CSI GLOBAL LTD.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at CSI GLOBAL LTD 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 CSI GLOBAL LTD
✨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 CSI GLOBAL LTD 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.
