Senior AI Engineer

We're an award-winning consultancy known for delivering exceptional products and services through technology. We work closely with organisations to help them accelerate value delivery and create outstanding customer experiences. Our purpose is simple: to empower organisations to make a real difference for people, society, and the planet through technology that's efficient, user-friendly, and solves problems fast. At Burendo, we believe that together, we can achieve incredible things.

What sets us apart is how we work. We pride ourselves on having a pragmatic attitude to delivery-we think big, plan practically, adapt quickly, and always focus on results, no matter how complex the challenge. We're passionate about making great things happen by embracing innovation, challenging the status quo, and fostering collaboration at every step. At Burendo, caring for people is at the heart of what we do.

We value partnerships, listen to different viewpoints, and believe in treating everyone fairly. And, we love to share what we learn-using our expertise to help others grow and empowering organisations to succeed in the long term. Great engineers come from many different backgrounds and are specialists in many different areas. At Burendo, we look for people who want to contribute to all areas of the tech stack and get involved in all stages of the software development lifecycle.

Join Burendo and make AI engineering the core of your day to day, across client work, internal builds, and bids.

These are the things we value most at Burendo, we can teach skills, but our behaviours forge the culture we strive for. A passion for engineering and AI, and a desire to keep learning A focus on writing clear, concise code that's easy to maintain, and being pragmatic when required, avoiding unnecessary  gold plating , including knowing when an AI solution isn't the right answer An understanding that quality is everyone's responsibility Comfortable working with others in pairing or mobbing scenarios A good communicator who shares our values of openness and respect A Dev Ops mentality, meaning that you don't want to chuck code over the fence, and you are keen to be involved right through to delivering the code to the customer

We believe every engineer should have a fundamental understanding of development, infrastructure, and testing and therefore you'll need at least some of these skills to help you pick the role up quickly.

Burendo is invested in the growth of our consultants and provide a healthy self-development budget you can use to grow in the areas mentioned below, or any other of your choosing!

• Fundamental coding experience in at least two of the following:
  Python, JavaScript, Node.js, C#, Java
• Experience engineering products or systems with AI layers, including LLM integration, agents, APIs, and data pipelines, either adding this to an existing product or building it into a new one
• Experience designing RAG architectures, including retrieval strategy, chunking, and grounding
• Experience working within cloud environments, specifically AWS or Azure (or both)
• A fundamental understanding of infrastructure as code with Terraform or an equivalent
• Experience working with CI/CD pipelines such as Git Hub Actions, GitLabCI, Jenkins, or Azure Dev Ops
• Experience supporting a live product
• Experience with database technologies, including vector databases and embeddings
• Experience testing and monitoring AI output quality systematically, including golden datasets, regression checks, and automated scoring

• Good understanding of and experience with agile methodologies
• Experience shipping production agentic or LLM based systems, including tool and function calling, state and memory management, control flow (branching, loops, retries), and human in the loop checkpoints, using a framework such as Lang Chain/Lang Graph, Amazon Bedrock Agent Core, CrewAI, Llama Index, Strands Agents, Google ADK, or OpenAI Agents SDK.
• Familiarity with MCP (Model Context Protocol) or similar standards for connecting AI models to external tools and data sources
• Basic data pipeline or ETL experience feeding data into AI systems
• Awareness of AI specific security, compliance, and governance considerations (data handling, model risk, responsible use policy), particularly relevant given our regulated sector clients
• Experience monitoring AI system performance and cost in production
• Awareness of fine tuning, when and why it's used, even without…