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Strong Tier-1 brand, mid-level backend title, and metro location increase candidate competition.
Requires deep Java backend, agentic AI integration, and financial services experience, limiting cross-industry transferability.
Explicit 6+ years, deep Java/Spring Boot, microservices, and required agentic AI experience make filters stringent.
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Build and maintain scalable backend Java enterprise applications using Spring Boot and microservices with strong focus on performance and concurrency.
Design and implement AI-assisted/agentic software workflows incorporating orchestrator/subagent patterns and LLM integrations in production systems.
Lead backend engineering efforts ensuring reliability, observability, and scalability in financial services technology environments.
6+ years of hands-on Java development experience with deep expertise in Spring Boot, microservices, REST APIs, messaging (Kafka, JMS, RabbitMQ), and strong SQL skills.
Practical experience integrating Large Language Models like OpenAI, Azure OpenAI, or Anthropic into backend systems; familiarity with agentic AI frameworks such as LangChain, LangGraph, or Claude Agent SDK.
Experience with concurrency, distributed systems, CI/CD pipelines, DevOps practices, and performance tuning.
Work Experience Required: Minimum 6 years in backend Java development with AI/agentic software exposure.
Experience working in or with Financial Services or Investment Banking domains, understanding domain-specific requirements and workflows.
Demonstrated ability to design complex multi-agent AI workflows including orchestrator/subagent patterns, agent-to-agent communication, and system guardrails.
Hands-on proficiency with Python for AI integration and familiarity with RAG architectures, vector databases, and AI system reliability concerns (e.g., hallucination mitigation, latency, observability).