About this role
Salary: £61,000 - 101,000 per year
Requirements: Expert-level experience building complex LLM-powered systems and multi-agent workflows using frameworks such as LangGraph, LangChain, AutoGen, or ADK.Deep practical understanding of machine learning algorithms, natural language processing techniques, and optimizing large language models for enterprise deployment.Strong proficiency in designing optimized ELT/ETL pipelines and managing data lake/data warehouse architectures.Hands-on experience with Google Cloud Platform services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage.Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes.Extensive experience leading technical delivery, defining engineering milestones, running code reviews, and mentoring junior or intermediate engineering talent.Works with high autonomy under broad strategic guidance and is accountable for defining and meeting technical, architectural, and delivery goals.Exerts major technical influence across the organization and partners with cross-functional business and product leaders.Manages diverse, highly complex, and unpredictable technical challenges using fundamental engineering principles.Advises executives on AI trends, risks, and tools and bridges technical and business teams with strong leadership, creativity, and ethical problem-solving.Advanced, production-grade proficiency in Python, including Pandas, NumPy, FastAPI, or Flask, with a focus on clean, modular, and highly testable code.Expert SQL querying, database design, partitioning, and optimization strategies for large-scale BigQuery environments.Desirable: Google Cloud Certified Cloud Engineer.Desirable: Google Cloud Certified Professional Data Engineer or Cloud AI Engineer.A Bachelors or Masters degree in Computer Science, Software Engineering, Artificial Intelligence, or a highly quantitative field is desirable, though proven experience shipping production-grade commercial AI systems may substitute.IT HNC/HND courses will also be accepted. Responsibilities: Design and scale robust, secure, production-ready multi-agent workflows, orchestrations, and advanced RAG architectures in collaboration with Enterprise Architecture principles.Drive delivery by designing and building agentic solutions from piloting through to full implementation.Establish coding standards, code review processes, testing frameworks, and evaluation metrics for generative AI applications.Support and enforce the standards set by the Head of Engineering and Technical Architect.Partner with GCP and Data Engineering teams to build LLMOps/MLOps CI/CD pipelines and scalable model deployment via Vertex AI and containerized environments.Own the building and maintenance of robust LLMOps pipelines.Implement evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise-grade safety, security, and compliance.Manage engineering workflows, CI/CD pipelines, version control, and evaluation frameworks for internal developer-facing AI assets, including prompt libraries and automated testing agents.Mentor intermediate and junior AI Engineers and foster a culture of continuous learning, clean code, and agility.Collaborate with the AI Product Owner and Business Analysts to translate business use cases into structured, achievable technical sprints.Shift the teams focus from proof-of-concepts to reliable, resilient production applications for global users.Support the companys evolving AI strategy by advising on use case identification, platform identification, and tool selection.Advise the AI portfolio lead on scaling impact and AI capability across the company.Stay up to date on market trends, new opportunities, and the changing AI landscape.Support use case design and feasibility assessments to ensure opportunities are achievable and scalable.Act as the execution arm for AI responsibilities and support other IT teams across the organisation. Technologies: AIARMArchitectBigQueryCI/CDCloudData WarehouseDockerETLFastAPIFlaskGCPSupportKubernetesLLMMachine LearningMLOpsProduct OwnerPythonRAGSQLSecuritynumpypandasAgentic AI More:
We are partnering directly with Rentokil Initial to hire for this role within our Group AI Team. We are scaling internal capabilities to deliver production-grade AI solutions across our global operations and are establishing an Agentic Factory: a high-velocity delivery team focused on genAI and ML solutions, multi-agent workflows, and automation systems. The role sits alongside our AI Delivery Manager, AI Product Owner, AI & Data Architect, and Head of Engineering, with a strong focus on technical leadership, mentorship, and hands-on delivery. We offer a competitive salary and bonus scheme, hybrid working, the Rentokil Initial Reward Scheme, 23 days holiday plus 8 bank holidays, an Employee Assistance Programme, death in service benefit, healthcare, and free parking. We are an equal opportunity employer and encourage applications from people from all backgrounds, with an inclusive environment that supports individuality and belonging.
last updated 37 week of 2026