AI Developer Agentic AI Engineer

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 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 testsregression tests and automated scoring. Reduce hallucinations and risk by implementing prompt policies constraintsstructured outputs and verification steps. Partner with risk slash compliance to ensure traceability audit logs explain abilityrequirements are Readiness and Operations

Implement observability for agents (latency cost tool failures drift qualitysignals escalation rates). Support CI/CD for agent prompts and configurations (versioning approvalsrollback). Collaborate with platform and security teams on secrets management accesscontrols PII protections and safe Qualifications 4 years of software engineering experience or equivalent with strong CSfundamentals Hands-on experience building with LLMs and modern AI app stack (agentsRAG 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 MilvusOpenSearch/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 controlscompliance audit readiness) Experience integrating with enterprise workflows (e.g. ServiceNow Customworkflow engines BPM/RPA) Familiarity with model evaluation approaches (LLM-as-judge rubric scoringretrieval evals offline/online testing) Experience with messaging/eventing (Kafka/SQS) email ingestion pipelines anddocument processing Exposure to MRM concerns and governance (model cards risk assessmentsvalidation processes)