AI Engineer # 26 - 00223

Duration: 12 months contract Pay Rate: 43 – 45 GBP/ hour Inside IR 35 (PAYE) About the Role We are seeking hands-on AI Engineers to design, develop, and deploy enterprise-grade Generative AI (GenAI) and Agentic AI solutions for complex financial services workflows. The role focuses on automating exception classification, root-cause analysis, impact assessment, workflow orchestration, and remediation across large-scale transaction and data-processing environments. You will work with structured and unstructured enterprise data, historical incidents, business rules, and workflow management systems to build intelligent, reliable, and scalable AI applications. Strong expertise in Python, SQL, API development, software engineering, and practical implementation of LLM-powered and agentic AI solutions is essential. Key Responsibilities

• Design and develop AI-powered workflows for exception classification, investigation, root-cause analysis, impact assessment, and remediation recommendations.
• Build agentic AI solutions incorporating workflow orchestration, tool/function calling, state management, and human-in-the-loop validation.
• Correlate new exceptions with historical incidents, known root causes, business rules, and transaction-level data to identify patterns and potential impacts.
• Develop Python- and SQL-based services to query, transform, validate, and analyse complex enterprise datasets.
• Integrate AI applications with enterprise APIs, relational databases, internal data sources, and workflow/ticketing platforms.
• Build reusable agent tools and services for information retrieval, investigation, analytical reasoning, and workflow execution.
• Implement Retrieval-Augmented Generation (RAG) to retrieve relevant regulatory documentation, historical issues, and internal knowledge repositories.
• Establish confidence scoring, validation mechanisms, guardrails, audit trails, and traceability for AI-generated outputs.
• Develop scalable backend services and APIs using Python and FastAPI.
• Implement testing, logging, exception handling, model evaluation, observability, and production-grade engineering practices.
• Collaborate with AI engineers, solution architects, business analysts, data engineers, and application teams across onshore and offshore environments. Required Qualifications
• 5–8 years of professional experience in software engineering, AI/ML engineering, data engineering, GenAI, or related technical roles.
• Strong hands-on experience developing production-quality applications using Python.
• Demonstrated experience building LLM/GenAI applications beyond proof-of-concept chatbots.
• Practical experience developing agentic AI workflows, reusable tools, and orchestration solutions.
• Strong SQL, data analysis, relational database, and data-processing capabilities.
• Experience building and integrating REST APIs, preferably using FastAPI.
• Strong understanding of software engineering principles, Git, debugging, testing, and application development.
• Experience working with structured and unstructured enterprise data, including JSON, transactional data, and operational datasets.
• Excellent analytical, problem-solving, and root-cause investigation skills.
• Ability to collaborate effectively with cross-functional technical and business stakeholders.
• A Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related discipline is preferred. Key Technical Skills Core Engineering
• Python – Strong/Expert
• SQL and Data Analysis – Strong
• REST APIs and FastAPI – Strong
• Git and Software Engineering – Strong
• Structured Data Processing and Transformation – Strong Generative AI and Agentic AI
• LLM and GenAI Application Development
• Agentic AI and Workflow Orchestration
• Tool Calling and Function Calling
• LangGraph, Google ADK, CrewAI, AutoGen, Semantic Kernel, or equivalent frameworks
• Retrieval-Augmented Generation (RAG) and Context Retrieval
• LLM Evaluation, Output Validation, and Guardrails
• Confidence-Based Classification and Semantic Matching
• Human-in-the-Loop Workflows and Approval Mechanisms Data and Enterprise Integration
• Complex SQL Queries and Relational Databases
• JSON, REST APIs, and Enterprise Application Integration
• Transactional, Event, and Operational Data Analysis
• Historical Incident and Workflow/Ticketing Data
• Data Correlation Across Multiple Sources
• Handling Incomplete, Inconsistent, and Evolving Enterprise Data Cloud and Production Engineering
• Exposure to AWS, Google Cloud Platform (GCP), or Microsoft Azure
• Logging, Monitoring, Observability, and Exception Handling
• Automated Testing, Evaluation, and Production Deployment Practices
• Auditability, Traceability, and Responsible AI Controls About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com .

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