Software AI Engineer

Key Responsibilities

• Design, develop and maintain AI-powered applications, intelligent agents and copilot solutions using Python.
  
• Build and integrate APIs, agent tools and Model Context Protocol (MCP) servers to connect AI applications with enterprise systems.
  
• Develop retrieval-augmented generation (RAG) pipelines, including document ingestion, embeddings, indexing and retrieval.
  
• Build and maintain data processing pipelines using Databricks and Apache Spark.
  
• Support the development, testing and deployment of machine learning models through MLOps pipelines.
  
• Develop user-facing AI interfaces, including streaming interactions and human-in-the-loop workflows.
  
• Implement automated testing, AI model evaluations and CI/CD processes to ensure application quality and reliability.
  
• Troubleshoot technical issues, optimise performance and maintain secure, scalable cloud-native applications.
  
• Collaborate with cross-functional engineering, data science and product teams to deliver high-quality AI solutions.
  

Experience & Skills Required

• 3+ years of commercial software engineering experience, with a strong background in application development and system design.
  
• Strong proficiency in Python, with experience in at least one additional language such as Java, TypeScript or SQL.
  
• Experience developing and integrating APIs, microservices and event-driven applications.
  
• Working knowledge of Generative AI, Large Language Models (LLMs), RAG, prompt engineering and AI agent frameworks.
  
• Experience working with large datasets and data processing technologies such as Apache Spark.
  
• Strong understanding of software testing, CI/CD, application security and operational resilience.
  
• Practical experience with cloud-native technologies, containers and Kubernetes.
  
• Experience working within Agile development environments.
  
• Understanding of secure software development practices and responsible AI principles.
  

Nice to Have

• Experience with AWS cloud services.
  
• Hands-on experience with Databricks and MLOps frameworks.
  
• Knowledge of Model Context Protocol (MCP) and AI agent orchestration.
  
• Experience with AI evaluation frameworks, LLM-as-a-judge techniques and automated regression testing.
  
• Familiarity with OpenTelemetry, observability and distributed tracing.
  
• Experience developing AI-powered copilots or enterprise GenAI applications.
  
• Exposure to financial services, banking or other highly regulated environments.
  
• Experience using AI-assisted development tools.