SDLC AI Engineer

Test Triangle Limited; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Test Triangle Limited in the United Kingdom seeks a Software Engineer to lead design and implementation of AI-driven workflows across the SDLC, leveraging the GitHub ecosystem and coding agents. You will architect and integrate advanced AI agents, ensure coding standards, and collaborate with cross-functional teams to embed AI-driven processes into core SDLC methodologies.

With hands-on experience in CI/CD integration and scalable prompt libraries, you will operate within enterprise-scale

Qualifications

• Experience with large-scale enterprise SDLC and transformation projects.
• Proficiency in Python or TypeScript with exposure to Rust/Golang/Java.
• Hands-on CI/CD integration and automation tooling with AI workflows.
• Ability to design agent-based architectures and scalable prompts.

Responsibilities

• Architect and maintain AI agents for coding and automation within GitHub workflows.
• Build evaluation frameworks to ensure that AI-driven solutions meet technical standards before deployment.
• Develop and govern prompt libraries, instruction sets, and standards for consistency.
• Integrate AI solutions with CI/CD pipelines and MCP servers for end-to-end development cycles.
• Collaborate with cross-functional teams to embed AI-driven processes into core SDLC methodologies.

Skills

Python

TypeScript

Rust

Golang

Java

GitHub

CI/CD

AI frameworks

Agent-based architectures

Tools

GitHub

Claude Code

Codex

CI/CD tooling

Job description

We are seeking a highly skilled Software Engineer with recentVibe coding experience to lead the design and implementation of intelligent solutions across the Software Development Life Cycle (SDLC), specifically leveraging the GitHub ecosystem. This role is focused on architecting and integrating sophisticated AI-driven workflows, including specialized coding agents, custom agents, and comprehensive Skills libraries, while ensuring all solutions adhere to rigorous engineering standards.

Key Responsibilities:

• AI Agent Engineering & Tuning:Architect and maintain advanced AI agents for coding and automation within GitHub workflows. This includes the active building, performance tuning, and refinementof agentic logic to ensure optimal performance.
• Evaluation & Quality Assurance:Implement robust evaluation frameworksto ensure that all AI-driven solutions meet established technical standards and best practicesbefore deployment.
• Standardisation (Prompt Ops):Develop and govern prompt libraries, instruction sets, and organizational standards to ensure consistency and reliability in AI usage across all engineering teams.
• System Orchestration:Integrate AI solutions seamlessly with CI/CD pipelinesand Model Context Protocol (MCP) serversto create automated, end-to-end development cycles.
• Strategic Collaboration:Partner with cross-functional engineering teams to embed AI-driven processesdirectly into core SDLC methodologies.

Technical Requirements:

• Programming Proficiency:Advanced expertise in Pythonor TypeScript. Professional experience with Rust, Golang, or Javais highly desirable.
• Ecosystem Expertise:Deep knowledge of the GitHub stack, Claude Code or Codex, including hands-on experience with CI/CD integrationand complex automation tools.
• Architectural Insight:A comprehensive understanding of AI frameworksand agent-based architectures, moving beyond simple prompts to multi-step agentic workflows.
• Engineering Standards:The ability to write clear, reusable prompts and Skills while maintaining the highest coding standardsand documentation.

have the candidates operated in large scale enterprise/industrial SDLC (large enterprises with complex process/tools). Given they need to apply their genAI skills in the context of a transformation from old to new…leading/guiding/designing how old style meets new style of engineering. Often we see inexperienced developers hopping onto Claude to be hyper productive but have limited insight how to apply that in the complex enterprise landscape like LBG.

Feedback for few profiles:

the first guy xxxxx - very terse, difficult to get coherent responses, very narrow exposure to SDLC - talked about agile but not the process of delivery - not a leader/shaper, a mid to junior level developer with claude on cv.

The second guy xxxxxx- had good/relevant experience some years ago, was better conversatonally, but lacked the kind of sharp/concise and relevant responses to direct questions about Enterprise SLDC, considerations towards agentic, etc. No doubt he has a rich career but don't see him facing into the CTO/CDAO leaders to address a particular complex assertion and value proposition. On reading the CV's i did have high hopes for those 2 but unfortunately the interviews lacked substance.