AI Engineer

As a Senior Consultant in SAIL, you will own and lead consultancy engagements end-to-end from shaping the opportunity and winning the work, through to delivery governance and team leadership. You will bring SME-level depth in at least one of AI/ML Engineering, Platform Engineering, or Software Engineering, and apply it to create real, lasting value for our clients.  

Although we do not expect you to be an expert in all of the below activities simultaneously, our team consists of people who can work as advisors to our clients as well as bringing deep technical knowledge when needed. The profile of our typical engagements reflects that.  

AI/ML Specialism 

You will bring expert-level knowledge in at least one of the following domains, and working knowledge across the others: 

 Agentic AI & LLM Engineering: 

• Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. 

• Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks.  

Machine Learning Engineering: 

• End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. 

• Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). 

Platform & Cloud Engineering: 

• Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure or GCP; experienced with containerisation, IaC, event-driven architectures and CI/CD. 

• Track record of delivering production Python services and APIs; working knowledge of cloud-native application patterns and release practices. 

 Software Engineering: 

• Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js, Material UI and SWR. 

• Cloud architecture design capability across major providers; rounded understanding of database trade-offs – relational, NoSQL, graph and caching strategies. 

• Strong engineering practices: CI/CD, testing (Jest, Cypress, React Test Library), release management and security-conscious development.  

• A genuine passion for AI solutions and specifically for the complexity of delivering them to production at scale. You should be as energised by the hard problems of operationalisation, reliability and governance as by the technology itself.
   

Your Skills and Experience  

We're seeking a technically credible, commercially aware consultant who brings a rare combination of delivery accountability, client advisory skill, and deep AI/technology specialism. You will be someone energised by the complexity of taking AI solutions to production at scale – and who can inspire a team and a client with that same passion. 

• 1-5 years in technology consulting, software engineering or AI/ML
   
• SME-level depth in at least one of: Agentic AI/LLM Engineering, Machine Learning Engineering, Platform & Cloud Engineering, or Software Engineering – with strong architecture and design capability across cloud, data and AI domains.
   
• Clear, confident communicator – able to make the complex accessible for technical and non-technical audiences alike, and to represent Baringa’s expertise with credibility. 

• Master’s degree in Computer Science, Engineering, Mathematics, Data Science or related discipline, or equivalent depth through relevant professional certifications (e.g. AWS Solutions Architect Professional, Google Professional ML Engineer). 

• Prior experience as a forward-deployed or embedded engineer within a client environment; exposure to regulated industries such as energy, financial services or public sector.