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We're hiring an AI Engineer to design and deliver production-grade GenAI and Agentic AI solutions across our public sector and enterprise clients. The successful candidate will work across AI Engineering disciplines including Generative AI, Agentic AI, Large Language Models and LLMOps as part of our growing AI Engineering team. You will work with architects, engineers and business stakeholders to deliver cloud-based AI solutions using GenAI and agentic systems, helping clients unlock data value, automate complex processes and drive digital transformation. Due to the nature of this role, successful candidates may need to undergo security clearance. To be eligible you must have lived in the UK for at least 5 consecutive years.
Job Responsibility:
Deploy, fine-tune and monitor Generative AI models and Agentic AI systems for enterprise use cases
Develop and implement Retrieval-Augmented Generation (RAG) pipelines and advanced prompt and context engineering strategies
Design and implement multi-agent systems using orchestration frameworks such as CrewAI, Semantic Kernel or LangGraph
Integrate Agentic AI into business workflows and collaborate with data engineers to bring agentic capabilities to production
Implement LLM evaluation pipelines to assess output quality, accuracy and safety
Apply responsible AI principles including fairness, transparency and auditability, particularly for regulated public sector environments
Apply AI safety, guardrails and output validation controls to ensure robust, compliant production deployments
Evaluate and recommend emerging GenAI tools and agentic frameworks for client applicability, driving innovation within the team
Requirements:
2+ years’ experience in AI engineering, software development or data science, with a strong recent focus on GenAI and LLMs
Hands-on experience with GenAI orchestration frameworks and cloud platforms, including Azure AI Foundry, CrewAI, LangChain, Semantic Kernel, Hugging Face and Azure ML Studio
Strong capability in prompt and context engineering, RAG pipeline design, and LLMOps, including tooling such as PromptFlow, LangSmith, prompt versioning and LLM cost management
Experience working with Azure data and analytics services, including Data Factory, Data Lake, Synapse Analytics and Azure SQL Database
Strong programming skills (Python, C# or similar), with experience using Azure DevOps/GitHub CI/CD, and working across the software development lifecycle, including access control, audit logging, documentation, knowledge transfer and training
Strong alignment with FSP values and ethos
Commitment to teamwork, quality and mutual success
Proactivity with an ability to operate with pace and energy
Strong communication and interpersonal skills
Dedication to excellence and quality
Nice to have:
Experience deploying AI solutions on Azure, including Azure OpenAI, Azure AI Foundry and Azure ML Studio, with familiarity using Microsoft Copilot Studio
Experience with ML and AI engineering toolchains, including MLflow, Databricks CLI, automated retraining pipelines, drift detection, MLSecOps, and LLM evaluation frameworks (e.g. RAGAS, DeepEval) alongside AI safety tooling (Azure Content Safety, Guardrails AI)
Experience with Infrastructure as Code (IaC) using Terraform, Bicep or ARM Templates to provision, manage and version cloud resources
Familiarity with agentic AI and ML technologies, including MCP (Model Context Protocol), tool-use patterns, Computer Vision (OCR/object recognition), core ML frameworks (TensorFlow, PyTorch, Scikit-learn)
What we offer:
Collaborative and supportive environment
Tools and opportunity to do work you can be proud of
Chance to work alongside some of the best people in the industry