Java Developer with AI

American IT Systems•Alpharetta, GA

20h•Hybrid

About The Position

Synechron is seeking a Java Developer with expertise in SQL, Apache Kafka, microservices architecture, and modern AI technologies. The role focuses on building scalable, high-performance, data-driven solutions using Java, Kafka, and cloud-native technologies, while applying AI, machine learning, and Generative AI to improve automation, analytics, decision-making, and application intelligence. The developer will integrate AI/ML services and Large Language Models (LLMs) with enterprise applications, APIs, databases, and real-time data platforms, collaborating with cross-functional teams to deliver innovative solutions and follow software engineering best practices. The position is based in Alpharetta, Georgia, with a hybrid schedule: three days working from the office and two days working from home. The role involves designing, developing, and maintaining Java microservices and data pipelines; integrating Kafka, databases, APIs, and AI services; deploying and operating containerized workloads; and supporting production systems.

Requirements

Proven Java development experience, preferably with Java 8 or higher, focused on data-intensive and distributed applications.
Strong SQL expertise, including complex queries, database optimization, indexing, and stored procedures.
Deep understanding of Apache Kafka architecture, including Kafka Streams, producer/consumer patterns, topic management, partitioning, replication, and schema management.
Hands-on experience integrating Kafka with microservices for real-time data processing.
Experience designing microservices architectures, RESTful APIs, and service-oriented applications.
Familiarity with Spring Boot, Spring Cloud, Spring AI, and related frameworks.
Experience integrating AI/ML models, APIs, or platforms into enterprise applications.
Understanding of Generative AI concepts, including LLMs, prompt engineering, embeddings, vector databases, RAG, and AI agents.
Experience with AI/ML frameworks or libraries such as Python, scikit-learn, TensorFlow, PyTorch, Hugging Face, or LangChain, or equivalent technologies.
Familiarity with vector databases and search technologies such as Pinecone, Milvus, Weaviate, OpenSearch, Elasticsearch, or pgvector, or equivalent platforms.
Knowledge of AI model deployment, monitoring, evaluation, versioning, and performance optimization.
Understanding of data privacy, security, governance, and responsible AI principles.
Proficiency with Docker and orchestration platforms such as Kubernetes.
Knowledge of relational databases, including MySQL and PostgreSQL, as well as NoSQL and vector databases.
Experience with DevOps practices and CI/CD pipelines, using Jenkins, GitLab CI, GitHub Actions, or equivalent tools.
Strong problem-solving skills, including diagnosing and optimizing database, messaging, application, and AI model performance.
Excellent communication skills and ability to work effectively with software engineers, data scientists, architects, and business stakeholders.

Nice To Haves

Experience building and deploying Generative AI applications using LLMs, RAG, AI agents, or conversational AI.
Experience integrating enterprise AI services such as Azure OpenAI, OpenAI, AWS Bedrock, or Google Vertex AI.
Experience with Spring AI, LangChain, LangGraph, LlamaIndex, or comparable AI application frameworks.
Experience with vector databases, semantic search, embeddings, and knowledge-base applications.
Familiarity with machine learning model lifecycle management, MLOps, and model monitoring.
Experience applying AI to real-time Kafka data streams for anomaly detection, classification, forecasting, or intelligent event processing.
Familiarity with message queuing systems such as RabbitMQ.
Contributions to open-source Java, Kafka, AI, or machine learning projects.
Experience implementing secure, scalable, production-ready AI solutions in cloud environments.

Responsibilities

Design, develop, and maintain Java-based microservices for data processing, real-time messaging, and AI-enabled functionality.
Architect and implement Kafka data pipelines using streams, topics, producers, and consumers for high-throughput, fault-tolerant data exchange and AI/ML workloads.
Write complex SQL queries and stored procedures, and optimize relational database operations.
Integrate microservices with Kafka messaging systems to provide reliable, secure, and scalable message flow.
Integrate AI and machine learning services, models, and APIs into Java applications and microservices.
Develop Generative AI solutions using LLMs, prompt engineering, RAG, embeddings, and vector search.
Build AI-powered features such as intelligent search, classification, summarization, recommendations, document processing, anomaly detection, and predictive analytics.
Design data preparation, ingestion, validation, and transformation workflows for AI/ML model training and inference.
Integrate applications with AI platforms such as Azure OpenAI, OpenAI, AWS Bedrock, or Google Vertex AI.
Implement model-serving and inference APIs with attention to latency, scalability, reliability, and secure access.
Apply responsible AI practices, including privacy, security, bias mitigation, explainability, monitoring, and protection from prompt injection and unauthorized data exposure.
Collaborate with product owners, architects, data scientists, and developers on scalable Kafka-, microservices-, and AI-based solutions.
Build and consume RESTful APIs and integrate third-party services while maintaining data consistency and integrity.
Use Docker and Kubernetes to deploy, scale, and manage microservices and AI workloads.
Write clean, documented code and follow best practices for database interactions, messaging, and AI service integration.
Conduct code reviews, enforce coding standards, and maintain software quality.
Troubleshoot production issues involving databases, Kafka message delivery, AI model performance, reliability, and latency.
Participate in Agile/Scrum teams and deliver features iteratively.
Stay current with developments in Java, SQL, Kafka, microservices, AI, machine learning, Generative AI, and data streaming.