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Java + AI Engineer

Artech
2 hours ago
Full-time
On-site
Chicago, Illinois, United States
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.