Sr AI Developer/Agentic AI Engineer
Accord Technologies Inc
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Charlotte, NC
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Mid-Senior level
Posted April 1, 2026
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Responsibilities
Commitments
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.
Commitments
Charlotte, NC (Need Onsite day 1, hybrid 3 days from office).
Inperson interview needed.
Position type: W2 contract
Not Met Priorities
What still needs stronger evidence
Requirements
- Collaborate with platform and security teams on secrets management, access controls, PIl protections, and safe deployments.
- 8+ years of software engineering experience or equivalent with strong CS fundamentals
- Very strong experience on Agentic AI Development.
- 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 Skills
- 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)
Education
- (Not required) – 8+ years of software engineering experience or equivalent with strong CS fundamentals
Sr AI Developer/Agentic AI Engineer
Charlotte, NC (Need Onsite day 1, hybrid 3 days from office).
Inperson interview needed.
Position type: W2 contract
Job Description
We are building an agentic Al 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 too/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
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
8+ years of software engineering experience or equivalent with strong CS fundamentals
Very strong experience on Agentic AI Development.
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)
Charlotte, NC (Need Onsite day 1, hybrid 3 days from office).
Inperson interview needed.
Position type: W2 contract
Job Description
We are building an agentic Al 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 too/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
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
8+ years of software engineering experience or equivalent with strong CS fundamentals
Very strong experience on Agentic AI Development.
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)