Agentic AI Developer (LLM/RAG) C2C requirements – New York, NY

Skills:- Python, LangGraph/Lang Chain, Agentic AI Solution Development, Knowledge and grounding (RAG)

Role 1 :- Agentic AI (LLM/RAG) Developer (Minimum 5 + Years Exp)

Role 2:- Lead Agentic AI (LLM/RAG) Developer  (Minimum 8 + Years Exp)

Location:- New York/New Jersey/North Carolina (Hybrid) 

Role Summary:- We are building an agentic AI platform to transform commercial banking customer service. The Al developer will design, build, and operate LLM-powered agents that interpret inbound servicing requests (e.g., email/case intake), retrieve grounded knowledge, and execute approved workflows through secure to/API integrations – with enterprise-grade controls, observability, and human-in-the-loop patterns.

This role sits within a cross-functional team with Product, Operations, Technology, and Risk partners and focuses on delivering production-ready agentic Al capabilities for regulated financial services

Responsibilities:- 

Agentic Al Solution Development

Build and enhance LLM/agent orchestration (Planner/supervisor patterns, tool-using agents, routing, guardrails).

Implement intent classification, information extraction, validation, and decision logic for servicing workflows

Developed tool calling integrations to downstream systems (CRM, workflow engine, core banking services, case management)

Implement human-in-the-loop workflows (review, approval, escalation, override) based on confidence/risk thresholds

Knowledge and grounding (RAG)

Design and implement retrieval-augmented generation (RAG) for policy procedure grounding and resolution guidance

Build knowledge ingestion pipelines with refresh/versioning

Improve answer quality via chunking strategies, embeddings re ranking and context management

Required Qualifications:-

4+ years of software engineering experience or equivalent with strong CS fundamentals

Hands-on experience building with LLMs and a modern AI app stack (agents, RAG, tool/function calling).

Strong proficiency in Python and building back-end services/APIs.

Experience with at least one: Lang Chain/LangGraph, Llamalndex, Semantic Kernel, or equivalent frameworks.

Experience with vector databases and search (e.g., Pinecone, Weaviate, Milvus, OpenSearch/Elastic)

Experience deploying services in cloud environments (AWS/Azure/GP) with basic DevOps practices

Strong understanding of security and privacy principles (PIl handling, least privilege, 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, Custom workflow 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, and document processing

Exposure to MRM concerns and governance (model cards, risk assessments, validation processes).