Senior AI Engineer (Agentic Systems)

🔒 Confidential Employer
Posted 3 May 2026
LOCATION
Not specified
TYPE
Full-time
LEVEL
Mid-Senior level
CATEGORY
Software Engineering
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

C# .NET Azure DevOps Distributed Systems AI-assisted Development Agentic Workflows Test Automation Code Review

FULL DESCRIPTION

Senior AI Engineer (Agentic Systems)

[Employer hidden — view at passion-project.co.uk] is hiring a Senior AI Engineer for a UK-based hybrid role. This is a full-time position within Product Development.

  • Work Type: Hybrid
  • Job Type: Regular - Full-time
  • Experience Level: Senior

Overview

At [Employer hidden], we build software that supports critical compliance needs for global clients. We are now embedding AI as a core capability across the entire software development lifecycle. We are seeking a Senior AI Engineer to lead the practical adoption and scaling of AI-assisted and agentic engineering across our teams. This is not a research or experimentation role. You will work hands-on within real codebases, using modern AI-native development environments (Cursor preferred) to fundamentally change how software is built, tested, and delivered. Your focus is to turn AI from a tool into a system. Repeatable, scalable, and embedded. You will define and implement playbooks, patterns, and workflows that enable teams to operate with parallel AI agents, autonomous code review, and AI-driven delivery pipelines. You will also help bootstrap new initiatives, ensuring they start with the right architecture, tooling, and AI-enabled engineering practices from day one. This role sits within R&D Engineering and partners closely with Platform, QA, and Product Engineering. Influence is earned through delivery, not hierarchy.

Responsibilities

  • Design and implement scalable AI-assisted engineering workflows across teams
  • Establish playbooks, standards, and best practices for agentic development
  • Build and operationalize task-specific agents (e.g. test generation, refactoring, code analysis), reusable skills, templates, and workflows, and multi-agent and parallel execution patterns
  • Integrate AI into CI/CD pipelines (Azure DevOps preferred), including autonomous or assisted code review, AI-driven test generation and maintenance, and code quality and compliance checks
  • Implement automation triggers and hooks to embed AI into the delivery lifecycle
  • Work directly within codebases to accelerate delivery and improve quality
  • Enable and upskill engineering teams through practical guidance, examples, and training
  • Bootstrap new projects with AI-first engineering practices and tooling
  • Rapidly prototype and validate new approaches, focusing on real delivery impact
  • Ensure all AI-enabled workflows are robust, observable, and production-safe

Skills and Experience

  • Core Engineering: Strong software engineering background (ideally C# / .NET) in cloud-based SaaS environments; experience building and operating distributed systems; strong understanding of APIs, system design, and modern development practices; experience with CI/CD pipelines (Azure DevOps preferred)
  • AI & Agentic Engineering: Hands-on experience using AI within real development workflows; deep familiarity with AI-native IDEs (Cursor preferred); proven experience designing structured AI workflows including reusable prompts, skills, templates, multi-step or agent-based execution patterns, tool integration and workflow orchestration; experience integrating AI into CI/CD pipelines, PR validation, automation, developer tooling; practical application to test generation, code analysis, refactoring, and developer productivity at scale
  • Delivery & Problem Solving: Track record of delivering production-grade solutions; experience enabling other engineers to adopt new technologies at scale; strong problem-solving skills; ability to define patterns where none exist and make them usable by others

Important Clarification: Experience limited to prompt-based tools used in isolation is not sufficient. We are looking for engineers who have embedded AI into real engineering systems and workflows and have scaled those practices across teams.

Minimum Qualifications

  • Software engineering experience in cloud-based SaaS environments
  • Experience designing and evolving enterprise-scale distributed systems
  • Demonstrated impact in improving engineering delivery or developer productivity
  • Practical experience applying AI within professional engineering workflows
  • Experience working within enterprise SaaS platforms
  • Right to work in the country of employment

Integrity and Ethics

All [Employer hidden] employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.

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