AI engineer for LLM systems

We believe in the power of ingenuity to build a positive human future. We challenge where it matters and own the outcome. We combine strategic thinking, customer-centric service design, and agile engineering practices to accelerate innovation in a tech-driven world.

• Work to agile best practices and cross-functionally with multiple teams and stakeholders.
• You’ll be using your technical skills to problem solve with our clients, as well as working on internal projects
• Live in-person whiteboarding sessions to problem solve as a team, alongside asynchronous communication on Teams
• Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic.
• Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs.
• Developing and testing agentic architectures through our own Genie Platform – enabling AI agents that reason, retrieve, and act across systems.
• Exploring LLMOps, evaluation tools, and model observability platforms like TruLens and LangSmith.
• Deploying solutions on modern cloud and DevOps environments (AWS, Azure, GCP) – but always choosing the right tools for the problem at hand.
• Constantly learning, testing, and sharing findings across our internal AI community.

• Software engineers with a passion for AI – or data scientists who’ve embraced engineering.
• People who experiment, prototype, and explore emerging AI tools in their own time.
• Strong foundation in a language suited to AI system development and data workflows.
• Experience integrating models with APIs, data sources, or production systems.
• Curiosity about LLMs, RAG pipelines (Graph & Vector based), and agent frameworks.
• Understanding of cloud-native (AWS / GCP / Azure) and DevOps / DevSecOps practices.
• A collaborative mindset and willingness to share, learn, and teach.
• Understanding of prompt and context engineering and model evaluation.
• Solid grasp of distributed systems, microservices, and RESTful APIs.
• An understanding of LLMOps tools for managing GenAI workflows.

• Hybrid working - our approach is to be in the office or on client site a minimum of 2 days per week.
• Grow a flexible and unique career within a trust-based, inclusive environment that values excellence, innovation, and curiosity. You have the option to progress with us on a technical career track. No need to go onto the Partner career track if this doesn’t align with what you want to do.
• Work on a broad variety of projects and tech stacks for clients across seven sectors - no project is ever the same
• Join other experts within our supportive and collaborative tech community through knowledge-sharing and peer-level support, coaching and mentoring
• Deepen your expertise through our culture of learning and growth – you’ll have budget to take courses (technical and non-technical training), plus gain certifications
• Hybrid working with the team on client site or in our office a minimum of two days per week. However, the actual time you spend and where you spend it will vary by role or assignment, including up to 5 days per week on a client site.
• Health and lifestyle perks accompanying private healthcare for you and your family
• 25 days annual leave (plus a bonus half day on Christmas Eve) with the opportunity to buy 5 additional days
• Generous company pension scheme
• Opportunity to get involved with community and charity-based initiatives
• Annual performance-based bonus
• PA share ownership
• Tax efficient benefits (cycle to work, give as you earn)