The Opportunity

We are looking for a hands-on Team Lead, AI & Automation to join Finance Data & Automation (FDA). You will own a major automation workstream for Finance and FinTech teams across AR/Collections, AP, Treasury, Tax and Accounting, from discovery and design through build, deployment and production support. Our estate is moving from traditional RPA (SS&C Blue Prism) to code-first, agentic AI automation: Python services, data pipelines and LLM-based agents that are observable, testable and SOX-compliant. You will build alongside the team while setting technical direction, reviewing solutions and coaching engineers.

Key Responsibilities

• Own an automation workstream end to end: intake, prioritisation, solution design, delivery plan, and measurable outcomes (hours saved, error reduction, straight-through processing, cycle time).

• Design, build, test and deploy automation using Python, APIs, SQL/data pipelines, workflow tools and RPA, picking the simplest approach that is reliable.

• Lead agentic AI solutions such as document extraction, classification, dispute/exception handling and query triage. Use LLM tool calling, MCP-based integrations and agent frameworks, with human-in-the-loop checkpoints, guardrails and evaluation before anything touches a financial record.

• Break down work, clarify ownership, and review designs and code across the team; set standards for testing, Git, code review and documentation.

• Coach and support team members, including engineers moving from RPA to code and AI development.

• Lead the migration of selected Blue Prism processes to code-based or agentic solutions without disrupting month-end and daily operations, while keeping existing bots stable.

• Own monitoring, alerting, exception handling, run logs, runbooks and PDD/SDD documentation so solutions are supportable.

• Build SOX/ITGC controls into each solution: change management, segregation of duties, least-privilege access and audit evidence.

• Partner with Finance SMEs, process owners, FinSys and Engineering to scope requests, manage expectations and report progress and value to leadership.

Requirements (must-have)

• Bachelor's degree in Computer Science, Engineering, Information Systems or a related field, or equivalent practical experience.

• 7+ years in software engineering, data engineering or intelligent automation, including production solutions you designed, delivered and supported end to end.

• Experience leading a workstream or small team: planning work, reviewing solutions and coaching others.

• Strong Python and SQL; experience with REST APIs/JSON, file/SFTP/email integrations and robust exception handling.

• Fluency in agentic AI development: you have built LLM-based agents or automations using tool/function calling, MCP or similar tool integration, and at least one agent framework (e.g. LangGraph, LangChain, Semantic Kernel, OpenAI Agents SDK). You also work productively with AI coding agents (Cursor, Claude Code or similar).

• Disciplined SDLC: Git, code review, automated testing, CI/CD and controlled releases.

• Experience with production support: monitoring, incident triage, root-cause analysis and clear stakeholder updates.

• Understanding of controlled environments (SOX or similar): audit trails, change control and access management.

• Strong stakeholder skills; able to explain technical trade-offs to Finance users and leadership in clear English.

Preferred Qualifications (nice-to-have)

• n8n or similar workflow automation tools (Power Automate, Make, Zapier).

• Hands-on SS&C Blue Prism (or UiPath/Automation Anywhere), and experience migrating RPA to code or cloud-native platforms.

• OCR/intelligent document processing; RAG with embeddings/vector search; LLM evaluation and cost/latency tuning.

• Big-data and analytics stores (StarRocks, Hadoop/Hive, Superset); containers/Kubernetes; private-cloud deployment.

• Finance domain knowledge (AR/collections, AP, reconciliations, treasury, month-end close) and Oracle ERP exposure.

• Process discovery, process mining or Lean Six Sigma experience.

Success in This Role

• A reliable, well-documented automation portfolio with clear monitoring and few incidents.

• Legacy RPA processes migrated to code or agentic solutions on schedule.

• Measurable reductions in manual effort, errors and cycle time.

• A stronger team: clear standards, good reviews, and engineers growing into AI development.

• Strong controls and clean audit outcomes.

Important Note About This Role

This is a hands-on lead role: you will build as well as guide. We value evidence that you shipped and ran real automation, technical judgment and the ability to build with AI, more than a long list of tools or certifications.