Urgent: Agentic AI Engineer - Java Background: Arlington, VA: Onsite: Only H1

Hello,

Job Title: Agentic AI Engineer - Java Background

Location: Arlington, VA (Onsite)

Job Type: Contract

Visa: Only H1 with Passport Number

Job Summary

We are seeking a Senior AI Engineer to design and build autonomous, agentic AI systems utilizing a strong foundational background in Java enterprise development.
You will bridge the gap between traditional robust backend architecture and cutting-edge Large Language Model (LLM) orchestration frameworks.

Key Responsibilities

Design Agentic Workflows: Build autonomous AI agents capable of planning, tool-use, reasoning, and multi-agent collaboration.
Develop Java AI Pipelines: Implement LLM orchestration using modern Java frameworks like LangChain4j, Spring AI, or Semantic Kernel.
Integrate Enterprise Systems: Connect AI agents to legacy enterprise systems, databases, and third-party APIs via secure Java microservices.
Optimize Vector Databases: Design and maintain Retrieval-Augmented Generation (RAG) pipelines using vector stores like Milvus, Qdrant, or Pinecone.
Manage Agent Memory: Implement short-term and long-term memory architectures for agents to maintain stateful context across conversations.
Ensure Guardrails & Safety: Enforce strict prompt engineering standards, semantic caching, and LLM evaluation frameworks to prevent hallucinations.
Scale Backend Architecture: Optimize high-throughput, asynchronous, and event-driven Java applications for low-latency AI responses

Technical Skills Required

Core Language: Expert-level proficiency in Java (version 17 or higher preferred).
AI Frameworks: Deep experience with LangChain4j, Spring AI, or Deep Java Library (DJL).
AI Concepts: Strong understanding of function calling, multi-agent frameworks, prompt routing, and RAG.
Ecosystem Tools: Experience integrating with LLM providers like OpenAI, Anthropic, or local models via Ollama/vLLM.
Enterprise Stack: Mastery of Spring Boot, Spring Cloud, Hibernate, and RESTful API development.
Data & Memory: Proficiency with SQL (PostgreSQL), NoSQL, and Vector Databases (PGVector, Chroma).
Streaming & Event-Driven: Experience with Kafka, RabbitMQ, or WebSockets for real-time agent communication.
DevOps & Cloud: Familiarity with Docker, Kubernetes, and cloud platforms like AWS, Azure, or GCP.