Artech

Java + AI Engineer

Company : Artech

Location : Hometown, IL, 60456

Job Type : Full Time

Date Posted : 22 September 2026

Request ID:71009-1
Title: Java + AI Engineer
Locations: Chicago, IL
Duration: 6 Months
Experience Requested: 7+ Years
Pay Range: $45.00-53.00/Hour on W2 (All inclusive) -
Applicant must be willing to work on W2.
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.