Al Developer / Agentic Al Engineer

[Bhanu PK]

Mail i'd : nbp...@gmail.com

Job Title: Al Developer / Agentic Al Engineer

Experience : 9+

Location: Charlotte NC - Need Local – F2F Interview either in Piscataway NJ/ Charlotte, but work location is Charlotte NC only

Candidates who can attend an in-person interview will be accepted.
Candidates with OPT EAD, H4 EAD, GC EAD, USC, or GC status may be submitted.

 

Our challenge

We are building an agentic AI platform to transform commercial banking customer service. The AI 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 tools/APIs, ensuring enterprise-grade controls, observability, and human-in-the-loop patterns.

This role is part of a cross-functional team comprising Product, Operations, Technology, and Risk partners, focused on delivering production-ready agentic AI capabilities for regulated financial services.

The Role

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

Quality, 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 ability requirements are met.

Production Readiness and Operations

• Implement observability for agents (latency, cost, tool failures, drift, quality signals, escalation rates).
• Support CI/CD for agent prompts and configurations (versioning, approvals, rollback).
• Collaborate with platform and security teams on secrets management, access controls, PIl protections, and safe deployments.

Requirements:

• 4+ years of software engineering experience or equivalent with strong CS fundamentals
• Hands-on experience building with LLMs and modern Al app stack (agents, RAG, tool/function calling).
• Strong proficiency in Python and building back-end services/APls.
• Experience with at least one: LangChain/ 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)

Preferred, but not required:

• Experience in financial services or regulated domains (risk controls, compliance).
• Familiarity with enterprise workflow integrations (e.g., ServiceNow, RPA, BPM).
• Knowledge of model evaluation techniques and testing approaches.
• Exposure to messaging/eventing systems (Kafka/SQS), document processing, and ingestion pipelines.
• Understanding of MRM governance, model cards, risk assessments, and validation processes.