VP, AI Automation Engineer

Responsibilities

• The AI Automation Engineer is a builder and owner of the Bank’s intelligent automation layer — designing agentic pipelines, multi-step AI workflows, and the prompt and evaluation frameworks that keep model outputs production-grade.
• You will own conversation design and live monitoring for voice agent buildout, drive the model ops half of the Bank’s Dev Ops model, and bring production-grade Python engineering depth alongside AI-specific expertise.
• Build and scale agentic workflows across Loans, Deposits, and Payments domains.
• Design multi-step, autonomous AI pipelines with dynamic decision-making and tool use.
• Implement human-in-the-loop (HITL) review gates and confidence scoring thresholds.
• Develop, version, and evaluate prompts for OpenAI and Anthropic (Claude) models.
• Apply LLM-based development patterns: tool/function calling, agent frameworks (Lang Chain, Lang Graph, Auto Gen), and retrieval-augmented generation (RAG).
• Build NLP-based intelligent document processing (IDP) pipelines — extraction, classification, and analysis for loan origination and deposit onboarding.
• Conduct prompt regression testing and maintain evaluation frameworks to detect output quality degradation.
• Monitor live workflow outputs, detect drift or quality degradation, and trigger rollbacks when performance thresholds break.
• Manage model and prompt version rollouts in coordination with Cloud Engineering release gates.
• Design conversation flows, voice persona prompts, and escalation routing rules for the call center voice agent.
• Monitor call containment rates, resolution quality, and escalation patterns in production.
• Apply NLP-based transcript analysis to continuously improve voice agent performance.
• Evaluate AI and automation vendors and frameworks, making informed build-vs-buy recommendations across the partner portfolio.
• Partner directly with business SMEs across all three domains to translate operational workflows into AI-executable rules.
• Write production-grade Python code with automated testing, error handling, logging, and full documentation.
• Mentor junior engineers and help establish engineering culture and delivery standards as the team scales.

• 5–8 years of software engineering or automation development experience with a strong foundation in Python and demonstrated ability to build and ship production-quality code.
• Hands‑on experience designing and delivering agentic or automation solutions via custom code, API orchestration, workflow engines, or AI frameworks.
• Demonstrated experience with LLM-based development patterns: prompt engineering, tool/function calling, agent frameworks (Lang Chain, Lang Graph, Auto Gen), RAG, and NLP-based document or transcript analysis.
• Hands‑on experience with Microsoft Azure AI workloads — Azure Functions, Logic Apps, Service Bus, Microsoft Foundry, Azure Data Factory, and Azure Dev Ops.
• Strong command of software engineering fundamentals: version control, automated testing, CI/CD, error handling, logging, and documentation.
• Experience in financial services or a regulated environment with practical familiarity with compliance, audit trail, model risk, and data governance requirements.
• Experience building or integrating voice AI / conversational AI solutions (preferred)
• Experience evaluating AI and automation vendors and contributing to build‑vs‑buy decisions (preferred)
• Microsoft Azure certification (Azure Developer Associate, Azure AI Engineer Associate) (preferred)