Senior Java AI Engineer – Generative AI & RAG

J2B Global LLC; Florida; On-site; USD 150,000 - 210,000; Full time

Job summary

J2B Global LLC in Lake Mary, Florida, is seeking a Senior/Lead Java AI Engineer to lead enterprise GenAI and retrieval-augmented generation initiatives on an onsite contract basis. You will design, build, and productionize AI solutions with a focus on accuracy, security, latency, and cost.

You will lead architecture discussions, mentor engineers, and drive the adoption of secure AI practices across teams while integrating with OpenAI and Azure AI services.

Qualifications

• 10+ years of enterprise software or application development experience.
• Strong hands-on experience with Java, Spring Boot, REST APIs, and microservices.
• Hands-on experience delivering LLM-based applications and production GenAI solutions.
• Strong knowledge of system prompts, few-shot prompting, prompt optimization, structured outputs, and context management.
• Experience integrating OpenAI APIs, Azure OpenAI, Azure AI services, or Azure AI Foundry.
• Experience with embeddings, vector search, vector databases, retrieval, grounding, and document processing.
• Ability to integrate and evaluate modern frontier AI models and model APIs.
• Working knowledge of Git, CI/CD, Docker, Kubernetes, and cloud deployment.
• Strong stakeholder communication, architecture, mentoring, and technical decision-making skills.

Responsibilities

• Design and develop enterprise-grade AI applications using Java, Spring Boot, REST APIs, and microservices.
• Integrate LLM and Generative AI capabilities into enterprise applications and business workflows.
• Develop and optimize system prompts, few-shot prompts, reusable prompt templates, structured outputs, and context-management strategies.
• Integrate with OpenAI APIs, Azure OpenAI, Azure AI services, Azure AI Foundry, and other frontier AI model APIs.
• Design and implement RAG solutions using embeddings, vector search, document retrieval, grounding, and citation patterns.
• Evaluate and optimize models and prompts for accuracy, groundedness, latency, scalability, security, and cost.
• Implement AI security controls to mitigate prompt injection, hallucinations, sensitive-data exposure, and unauthorized access.
• Build production-ready logging, tracing, monitoring, observability, fallback, and error-handling mechanisms.
• Lead architecture discussions, code reviews, technical troubleshooting, and production issue resolution.
• Collaborate with business, product, architecture, and engineering stakeholders to move AI solutions from proof of concept to production.
• Mentor engineers and establish reusable standards for secure AI integration and application development.

Skills

Java

Spring Boot

REST APIs

Microservices

LLMs

Prompt engineering

OpenAI APIs

Azure OpenAI

Azure AI services

Azure AI Foundry

Embeddings

Vector search

Documentation

Tools

OpenAI APIs

Azure OpenAI

Azure AI services

Azure AI Foundry

Git

CI/CD

Docker

Kubernetes

Azure DevOps

GitHub

Maven

Gradle

Vector databases

Oracle

SQL

Job description

J2B Global LLC is seeking a Senior/Lead Java AI Engineer (Generative AI & RAG) for an onsite role in Lake Mary, FL on a contract basis. This position centers on building enterprise-grade GenAI and retrieval-augmented generation capabilities with strong technical leadership, security focus, and production readiness.

What you’ll build

You will design and develop enterprise Generative AI and RAG solutions, integrating LLM capabilities into business workflows. The work covers everything from prompt and context design to vector search, evaluation, and production observability, with an emphasis on accuracy, groundedness, latency, scalability, security, and cost.

Responsibilities

• Design and develop enterprise-grade AI applications using Java, Spring Boot, REST APIs, and microservices.
• Integrate LLM and Generative AI capabilities into enterprise applications and business workflows.
• Develop and optimize system prompts, few-shot prompts, reusable prompt templates, structured outputs, and context-management strategies.
• Integrate with OpenAI APIs, Azure OpenAI, Azure AI services, Azure AI Foundry, and other frontier AI model APIs.
• Design and implement RAG solutions using embeddings, vector search, document retrieval, grounding, and citation patterns.
• Evaluate and optimize models and prompts for accuracy, groundedness, latency, scalability, security, and cost.
• Implement AI security controls to mitigate prompt injection, hallucinations, sensitive-data exposure, and unauthorized access.
• Build production-ready logging, tracing, monitoring, observability, fallback, and error-handling mechanisms.
• Lead architecture discussions, code reviews, technical troubleshooting, and production issue resolution.
• Collaborate with business, product, architecture, and engineering stakeholders to move AI solutions from proof of concept to production.
• Mentor engineers and establish reusable standards for secure AI integration and application development.

Requirements

• 10+ years of enterprise software or application development experience.
• Strong hands-on experience with Java, Spring Boot, REST APIs, and microservices.
• Hands-on experience delivering LLM-based applications and production GenAI solutions.
• Strong knowledge of system prompts, few-shot prompting, prompt optimization, structured outputs, and context management.
• Experience integrating OpenAI APIs, Azure OpenAI, Azure AI services, or Azure AI Foundry.
• Experience with embeddings, vector search, vector databases, retrieval, grounding, and document processing.
• Ability to integrate and evaluate modern frontier AI models and model APIs.
• Working experience with Oracle, SQL, data-access layers, and enterprise persistence patterns.
• Understanding of AI security, data privacy, access control, prompt-injection mitigation, and responsible AI practices.
• Working knowledge of Git, CI/CD, Docker, Kubernetes, and cloud deployment.
• Strong stakeholder communication, architecture, mentoring, and technical decision-making skills.

Technologies

Java, Spring Boot, REST APIs, microservices, LLMs, prompt engineering, OpenAI APIs, Azure OpenAI, Azure AI services, Azure AI Foundry, embeddings, vector search, vector databases, Oracle, SQL, Git, CI/CD, Docker, Kubernetes, Azure DevOps, GitHub, Maven, Gradle, OpenAI, Azure AI

Preferred skills

• Experience with AI agents, tool/function calling, orchestration frameworks, and structured model outputs.
• Experience developing LLM evaluation frameworks and monitoring model quality, groundedness, latency, token usage, and cost.
• Experience deploying AI-enabled microservices in regulated or large-scale enterprise environments.
• Familiarity with Azure DevOps, GitHub, Maven or Gradle, and automated deployment pipelines.

Expected candidate profile

• Approximately 60–70% hands‑on engineering, with the ability to independently own solution design and delivery.
• Ability to explain end-to-end LLM or RAG architecture, including associated security controls.
• Delivered at least one Generative AI use case from proof of concept toward production deployment.
• Comfortable working onsite and collaborating with business, architecture, product, and engineering stakeholders.
• Strong analytical, troubleshooting, communication, and mentoring capabilities.

Location and eligibility

• Location: Lake Mary, FL (onsite)
• Visa: US Citizen, Green Card, or GC-EAD