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.