Skip to main content
David Careers

Java AI Engineer

Posted 13 days ago

futran tech solutionsAustin (TX)
Software DevelopersCustom Computer Programming Services

SENIORITY

Lead

Apply (opens in a new tab)

About the role

Java AI Engineer We are seeking a highly skilled Java AI Engineer to design, develop, and deploy AI-powered enterprise applications using Java technologies and modern Generative AI frameworks. The ideal candidate should possess strong expertise in Java, Spring Boot, Microservices, Cloud Technologies, Large Language Models (LLMs), AI Agents, and Retrieval-Augmented Generation (RAG) architectures. The role involves building intelligent business solutions, integrating Generative AI services, developing AI agents, and delivering scalable cloud-native applications for enterprise customers.
Key Responsibilities:
  • Design, develop, and maintain enterprise applications using Java, Spring Boot, and Microservices.
  • Build and integrate AI-powered applications using OpenAI, Azure OpenAI, and other LLM platforms.
  • Develop AI chatbots, virtual assistants, enterprise copilots, and intelligent search solutions.
  • Design and implement RAG (Retrieval-Augmented Generation) solutions using vector databases.
  • Develop AI agents and orchestration workflows using LangChain4j, Spring AI, AutoGen, or similar frameworks.
  • Create RESTful APIs and backend services for AI applications.
  • Implement prompt engineering and model optimization techniques.
  • Collaborate with Product Owners, Architects, Data Engineers, and Business stakeholders.
  • Deploy and manage AI workloads on cloud platforms.
  • Ensure application performance, scalability, security, and compliance.
  • Participate in code reviews, architecture discussions, and Agile ceremonies.
  • Troubleshoot and optimize AI application performance and operational costs.
  • Required Technical SkillsCore Java Technologies
  • Java 11/17/21 Spring BootSpring MVCSpring Security
  • Spring Data JPAHibernateRESTful Web Services
  • Microservices Architecture
  • MavenGradleAI / Generative AIOpenAI APIsAzure OpenAI Service
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)AI AgentsLangChain4jSpring AISemantic Kernel (Optional)
  • Vector Databases:
Pinecone ChromaDBWeaviateMilvusAI Model Evaluation and Monitoring Cloud Technologies Microsoft AzureAWSGCPAzure AI Services Azure AI SearchAzure Functions Kubernetes (AKS / EKS / GKE)API Gateway Cloud Storage Services Database TechnologiesSQL ServerOraclePostgreSQLMySQLMongoDBCosmos DBDevOps & Automation GitGitHubAzure DevOpsJenkinsDockerKubernetesSonarQubeCI/CD Pipelines
Preferred Skills: Experience building Enterprise AI Copilots. Knowledge of Machine Learning and MLOps. Experience with Apache Kafka and Event-Driven Architecture. Exposure to Databricks and Data Engineering concepts. Knowledge of OCR, Speech-to-Text, and Document Intelligence solutions. Experience with Power Platform and Copilot Studio integrations. BFSI, Capital Markets, Wealth Management, or Banking domain experience. Understanding of Responsible AI and AI Governance frameworks.

Before you apply

Applying takes about a minute. These four things decide how fast it moves after that.

Your profile is current

It's what we read first. Occupations, seniority and locations matter more than a long history.

Two examples you can talk through

Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.

A number in mind

What you're on now and what would make you move. We negotiate better when we know both.

Your notice period

Employers plan around it, and it's the question that stalls offers most often.

Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.

More like this