AI Developer / Agentic AI Engineer
AI Developer / Agentic AI EngineerRole SummaryWe are building an agentic AI platform to transform commercial banking customerservice. The AI developer will design, build, and operate LLM-powered agents thatinterpret inbound servicing requests (e.g., email / case intake), retrieve groundedknowledge, and execute approved workflows through secure tool/API integrations - withenterprise-grade controls, observability, and human-in-the-loop patterns.This role sits within a cross-functional team with Product, Operations, Technology, andRisk partners and focuses on delivering production-ready agentic AI capabilities forregulated financial servicesResponsibilitiesAgentic AI Solution Development• Build and enhance LLM/agent orchestration (Planner/supervisor patterns, tool-using agents, routing, guardrails).• Implement intent classification information extraction validation and decision logicfor servicing workflows• Developed tool calling integrations to downstream systems (CRM, workflowengine, core banking services, case management)• Implement human-in-the-loop workflows (review, approval, escalation, override)based on confidence/risk thresholdsKnowledge and grounding (RAG)• Design and implement retrieval-augmented generation (RAG) for policyprocedure grounding and resolution guidance• Build knowledge ingestion pipelines with refresh/versioning• Improve answer quality via chunking strategies, embeddings re ranking andcontext managementQuality, Safety and Evaluation• Define and run evaluation frameworks: golden datasets, scenario tests,regression tests, and automated scoring.• Reduce hallucinations and risk by implementing prompt policies, constraints,structured outputs, and verification steps.• Partner with risk slash compliance to ensure traceability, audit logs, explain abilityrequirements are met.Production Readiness and Operations
• Implement observability for agents (latency, cost, tool failures, drift, qualitysignals, escalation rates).• Support CI/CD for agent prompts and configurations (versioning, approvals,rollback).• Collaborate with platform and security teams on secrets management, accesscontrols, PII protections, and safe deployments.Required Qualifications• 4+ years of software engineering experience or equivalent with strong CSfundamentals• Hands-on experience building with LLMs and modern AI app stack (agents,RAG, tool/function calling).• Strong proficiency in Python and building back-end services/APIs.• Experience with at least one: LangChain / LangGraph, Llamalndex, SemanticKernel or equivalent frameworks.• Experience with vector databases and search (e.g., Pinecone, Weaviate, Milvus,OpenSearch/Elastic, pgvector)• Experience deploying services in cloud environments (AWS/Azure/GCP) withbasic DevOps practices• Strong understanding of security and privacy principles (PII handling, leastprivilege, audit logging)Preferred Qualifications• Experience in financial services or other regulated domains (risk controls,compliance audit readiness)• Experience integrating with enterprise workflows (e.g., ServiceNow, Customworkflow engines, BPM/RPA)• Familiarity with model evaluation approaches (LLM-as-judge, rubric scoring,retrieval evals, offline/online testing)• Experience with messaging/eventing (Kafka/SQS), email ingestion pipelines, anddocument processing• Exposure to MRM concerns and governance (model cards, risk assessments,validation processes)
