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Lead AI Engineer

Reveille TechnologiesLake Mary, FL🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeOn Site
LocationLake Mary, FL, United States
DockerMicroservicesOracleSQLSpringSpring BootGitJavaLLMGenerative AIRESTAzureKubernetesPrompt EngineeringCI/CDAzure DevOpsMavenRAG

Job description

Role Overview

We are seeking experienced Senior / Lead AI Engineers to design, build, and productionize enterprise Generative AI solutions. This onsite role combines strong Java and Spring Boot engineering with hands-on expertise in LLMs, prompt engineering, OpenAI and Azure AI integration, RAG, AI security, and model evaluation. The engineer will collaborate directly with business, architecture, product, and engineering stakeholders in Lake Mary.

Key Responsibilities

· Design and develop enterprise-grade AI-enabled applications using Java, Spring Boot, REST APIs, and microservices.

· Build and integrate LLM and Generative AI capabilities into business applications and workflows.

· Develop and optimize system prompts, structured prompts, few-shot prompts, reusable prompt templates, and context-management strategies.

· Integrate applications with OpenAI APIs, Azure OpenAI, Azure AI services, and other frontier AI models.

· Design and implement RAG solutions using embeddings, vector search, document retrieval, grounding, and citation patterns.

· Evaluate models and prompts for accuracy, groundedness, latency, scalability, security, and cost.

· Implement safeguards for prompt injection, sensitive-data exposure, hallucination, authentication, authorization, and responsible AI usage.

· Create production-grade logging, tracing, observability, model-response monitoring, fallback, and error-handling mechanisms.

· Lead architecture discussions, code reviews, technical troubleshooting, and production issue resolution.

· Partner with onsite stakeholders to refine use cases, communicate trade-offs, and move solutions from proof of concept to production.

· Mentor engineers and establish reusable standards for AI integration and secure application development.

Required Technical Skills

Skill Area

Requirement

Overall Experience

10+ years in enterprise software or application development.

Generative AI

Hands-on delivery experience with LLM-based applications and production GenAI use cases.

Prompt Engineering

Strong knowledge of system prompts, few-shot prompting, prompt optimization, context management, and structured outputs.

Java / Spring

Strong hands-on experience with Java, Spring Boot, REST APIs, and microservices.

OpenAI / Azure AI

Experience integrating OpenAI APIs, Azure OpenAI, Azure AI services, or Azure AI Foundry.

RAG

Experience with embeddings, vector search or vector databases, retrieval, grounding, and document processing.

Frontier Models

Ability to integrate and evaluate modern frontier AI models and model APIs.

Oracle

Working experience with Oracle, SQL, data-access layers, and enterprise persistence patterns.

Security

Understanding of AI security, privacy, access control, prompt-injection mitigation, and responsible AI practices.

DevOps

Working knowledge of Git, CI/CD, Docker, Kubernetes, and cloud deployment.

Leadership

Strong stakeholder communication, architecture, mentoring, and technical decision-making skills.

Preferred Skills

· Experience with AI agents, tool/function calling, orchestration frameworks, and structured model outputs.

· Experience defining LLM evaluation frameworks and monitoring 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.

· Can clearly explain an end-to-end LLM or RAG architecture and associated security controls.

· Has moved at least one GenAI use case from proof of concept toward production deployment.

· Comfortable working onsite with business, architecture, product, and engineering stakeholders.

· Strong analytical, troubleshooting, communication, and mentoring capabilities.

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