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Java + AI Engineer

Artech
3 hours ago
Full-time
On-site
Chicago, Illinois, United States
Java + AI Engineer

We are seeking a Java + AI Engineer to design, develop, and deploy AI/ML and Generative AI solutions, including LLM-based applications, RAG pipelines, predictive models, and AI agents. The ideal candidate will translate business requirements into production-ready AI solutions while ensuring scalability, security, and compliance. Key Responsibilities: Design, develop, and deploy Generative AI/ML solutions, including LLM-based applications, retrieval-augmented generation (RAG) pipelines, embeddings, and AI agents. Translate business use cases into production-ready AI solutions with measurable outcomes. Implement LLM orchestration, prompt engineering, vector search, and model fine-tuning. Develop scalable APIs and microservices to integrate AI capabilities into enterprise applications. Collaborate with Data Engineers, Data Scientists, Product Owners, and Cloud teams across onshore/offshore models. Implement MLOps / LLMOps practices, including CI/CD, monitoring, versioning, model governance, and observability. Ensure Responsible AI, security, compliance, and data privacy by design. Support production deployments, performance tuning, and continuous improvement of AI systems. Required Skills: Experience in software engineering, ML engineering, or AI solution development. Strong proficiency in Java, including Java Streams. Hands-on experience with Generative AI / LLMs, including RAG, embeddings, prompt engineering, and agents. Solid understanding of data engineering concepts, SQL/NoSQL, and feature pipelines. Experience deploying AI solutions on cloud platforms (GCP preferred; AWS/Azure acceptable). Familiarity with Docker, Kubernetes, and CI/CD pipelines. Strong problem-solving, communication, and stakeholder collaboration skills. Preferred Skills: Experience with MLOps/LLMOps frameworks. Knowledge of enterprise AI governance and compliance standards. Exposure to cross-functional agile teams and production AI deployment environments.