AI Developer

About The Role

We are seeking an AI Developer for a healthcare client. This position is available as a hybrid role near Cleveland, OH (3 days onsite, 2 remote), or fully remote.

• Duration: 6 months with the possibility to extend or convert to permanent.
• Conversion: Must be willing to convert to permanent after 6 months; client will provide sponsorship.
• Pay Rate: $85 - $90/hr.
• Hours: 8:00 AM - 5:00 PM EST.

We are seeking an AI Developer to design, build, and deploy modern AI-enabled solutions that leverage enterprise data across cloud and hybrid environments. This role will focus on developing scalable AI applications, including retrieval‑augmented generation (RAG), intelligent data pipelines, vector‑based search, and cloud‑native ML/AI systems.

• Design and develop AI‑powered applications using modern ML/AI engineering practices, including RAG architectures, vector search, and feature management.
• Build and maintain scalable data pipelines to support AI and analytics workloads, including ETL/ELT, streaming, and lakehouse patterns.
• Develop and integrate solutions across cloud, hybrid, and legacy enterprise systems, including ERP, mainframe, and CDC‑based ecosystems.
• Implement and manage vector databases, orchestration frameworks, and feature stores to support production AI use cases.
• Partner with platform and infrastructure teams to deploy solutions using containerization, Kubernetes, and infrastructure as code.
• Ensure strong data governance, including lineage, cataloging, and access controls for enterprise AI data assets.
• Optimize architecture for performance, scalability, and cloud cost efficiency.
• Collaborate with stakeholders to translate requirements into practical AI solutions.

• 3+ years of experience in software engineering, data engineering, or AI/ML development.
• Hands‑on experience building AI or data‑driven applications in enterprise environments.
• Strong proficiency in Python, SQL, or Java.

• Core: RAG, ELT/ETL, Data Pipelines, Vector Search, AI/ML Model Deployment.
• Infrastructure: Docker, Kubernetes, Terraform, IaC, CI/CD.
• Data: Vector Databases (e.g., Pinecone, Milvus), Streaming/Real‑time processing, Lakehouse Architecture, Data Cataloging.
• Platforms: AWS, Azure, or GCP.

• Bachelor's Degree in Computer Science, Software Engineering, Data Science, Electrical Engineering, or Computer Engineering.
• Preferred:
  Master's or PhD in Computer Science, Data Science, AI, or Machine Learning.