Integration Engineer AI Agents & Backend Platforms

ROLE OVERVIEW

As an Integration Engineer (Band 7A) deployed to Innovation team, you will build autonomous AI agent systems that perceive environments, make decisions, use tools and execute multi-step workflows with minimal human intervention. You will specialise in LLMs, prompt engineering and Retrieval-Augmented Generation (RAG) to create intelligent agents that automate complex tasks across customer service, data analysis and software development domains.

Two resources are required at this band level to support the breadth of AI agent development, system integration and backend platform work within the team.

KEY RESPONSIBILITIES

• Develop Autonomous Agents: Design and implement intelligent agents capable of planning, reasoning and achieving specific goals independently.
• System Integration: Connect AI agents to external APIs, databases and software tools to perform real-world actions within enterprise workflows.
• Optimise Performance: Fine-tune models, improve prompt engineering and enhance RAG (Retrieval-Augmented Generation) architectures.
• Evaluation & Testing: Build frameworks to evaluate agent performance, reliability and safety across automated workflows.
• Maintain Guardrails: Ensure safe operation and proper oversight in automated workflows, including safety controls and escalation mechanisms.
• Backend Development: Contribute to microservices architecture, database design and system integration underpinning agent platforms.
• Deconstruct complex business tasks into relevant steps for AI implementation, working with product and business stakeholders to define agentic workflows.

ESSENTIAL SKILLS & EXPERIENCE

• Proficiency in Python and related AI/ML frameworks; experience in API design and working with Large Language Models (LLMs).
• Understanding of machine learning principles, data structures and algorithms relevant to AI agent design.
• Strong backend proficiency: experienced with databases, microservices and distributed system architecture.
• Ability to deconstruct complex business tasks into structured steps suitable for AI-driven implementation.
• Bachelor's degree in Computer Science, Software Engineering, Information Technology or a related field (or equivalent experience).
• At least 8 years in software engineering, with 5+ years focused on designing and building scalable systems.
• Experience leading engineering initiatives with a track record of driving technical decisions and establishing engineering standards.

DESIRABLE SKILLS

• Hands-on experience with agentic frameworks (e.g. LangChain, AutoGen, CrewAI, or equivalent).
• Experience with RAG pipelines, vector databases and embedding models.
• Experience integrating AI systems with enterprise APIs, CRM, ERP or workflow platforms.
• Knowledge of AI safety, responsible AI principles and guardrail implementation.
• Familiarity with cloud-native development (AWS, Azure or GCP) and containerised deployment.