Senior Infrastructure Support Analyst in London

A leading financial services client in London is seeking a talented AI Automation Engineer to join their team. The role requires analysing and optimising business processes for automation while designing, building, and deploying intelligent automation solutions using BPA platforms (Appian), Machine Learning, and Generative AI to drive operational efficiency and innovation.

Key Responsibilities

• Process Analysis & Optimisation – Analyse existing business processes through stakeholder interviews, process mapping and workflow documentation to identify automation opportunities. Create process flow diagrams, conduct time‐motion studies, identify bottlenecks and redesign processes to be machine‐readable and automation‐ready.
• Python Development – Write clean, maintainable Python code (object‐oriented, asynchronous, error handling) using libraries such as Pandas, NumPy, requests, asyncio, pytest, and proper logging. Build robust automation scripts with documentation.
• AI & Machine Learning Frameworks – Build, train and deploy models using TensorFlow, PyTorch, scikit‐learn and Hugging Face Transformers for classification, regression, clustering and NLP tasks. Apply model evaluation, hyperparameter tuning, feature engineering and MLOps practices for production deployment.
• Generative AI & LLM Integration – Work with OpenAI GPT, Anthropic Claude, Azure OpenAI, Llama and Mistral models. Perform prompt engineering, fine‐tuning, RAG architectures, vector database integration (Pinecone, ChromaDB, FAISS), embeddings and build AI‐powered automation solutions that leverage natural language understanding.
• Appian BPA Platform – Design processes, interfaces, rules, integration objects and data models within Appian. Build end‐to‐end business process applications, configure workflows, implement business rules, manage records and integrate Appian with external systems via REST APIs, web services and connected systems.
• API Development & Integration – Design and build RESTful APIs with FastAPI, Flask or Django REST Framework. Handle authentication (OAuth, JWT), rate limiting, error handling, Swagger/OpenAPI documentation, webhooks and integrate disparate systems to create seamless automated workflows.
• Document Processing & OCR – Implement intelligent document processing solutions using OCR technologies such as Tesseract and Azure AI Document Intelligence. Build pipelines for automated ingestion, processing, extraction and validation of documents.
• Robotic Process Automation – Apply RPA tools (UiPath, Automation Anywhere, Power Automate) for screen scraping, legacy system integration, and build hybrid automation solutions. Choose when to combine RPA, APIs or AI for optimal results.
• Data Engineering & Pipeline Development – Construct data pipelines (ETL) using SQL Server, Azure Data Factory and other tools. Ensure data quality, validation and transformation for machine learning applications.
• Machine Learning Operations (MLOps) – Deploy ML models to production via Docker, Kubernetes, MLflow or DVC. Monitor model performance, drift, conduct A/B testing and implement CI/CD pipelines for automated model training and deployment.
• Solution Architecture & Technical Design – Design end‐to‐end automation architectures merging BPA, ML, GenAI and APIs. Create technical design documents, architecture diagrams, evaluate build‐vs‐buy, estimate effort and present recommendations to stakeholders.
• Stakeholder Collaboration & Change Management – Communicate with business users, translate requirements into technical specs, demonstrate PoCs, manage expectations, conduct UAT, provide training, measure automation ROI and drive adoption of intelligent automation across the organisation.

If you align to the key requirements then please apply with an updated CV.