Insight International (UK) Ltd
Senior AI Platform Architect – Agentic SDLC Automation
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Senior AI Platform Architect – Agentic SDLC Automation
Location: London, UK - Hybrid 2 to 3 days
Employment Type: Permanent
The Role
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.
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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
The candidate should have hands-on experience with the following:
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
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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
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