AI Developer / Agentic AI EngineerWe 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 tool/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 AI capabilities for regulated financial servicesResponsibilitiesBuild and enhance LLM/agent orchestration (Planner/supervisor patterns, tool-using agents, routing, guardrails).Implement intent classification information extraction validation and decision logic for servicing workflowsDevelop 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 thresholdsKnowledge and Grounding (RAG)Design and implement retrieval-augmented generation (RAG) for policy procedure grounding and resolution guidanceBuild knowledge ingestion pipelines with refresh/versioningImprove answer quality via chunking strategies, embeddings re ranking and context managementQuality, Safety and EvaluationDefine 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 OperationsImplement 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, PII protections, and safe deployments.Required Qualifications4+ years of software engineering experience or equivalent with strong CS fundamentalsHands-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, Semantic Kernel 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) with basic DevOps practicesStrong understanding of security and privacy principles (PII handling, least privilege, audit logging)Preferred QualificationsExperience 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 processingExposure to MRM concerns and governance (model cards, risk assessments, validation processes)Kaleidoscope, an Infosys Company, is an equal opportunity employer, and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, spouse of protected veteran, or disability.