Sr. Java Full Stack AI Engineer
Digipulse Technologies Inc.
Newport, KY, United States
10 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Artificial Intelligence
Amazon Web Services
Microsoft Azure
Cloud Computing
Cloud Engineering
Information Engineering
Data Infrastructure
Data Stores
DevOps
Programming Tools
Distributed Systems
+18 more
Python (Programming Language)
Machine Learning
Node.Js
Web Applications
Google Cloud
Cloud Platform System
GitHub Copilot
Large Language Models
Prompt Engineering
Backend
Kubernetes
Enterprise Integration
Machine Learning Operations
Claude
Api Design
Google Gemini
Data Pipelines
Programming Languages
Requirements
- Strong backend engineering background (role is heavily backend-focused)
- Hands on experience with programming languages such as Java, Node.js, Python
-
Hands-on experience deploying and scaling applications within cloud environments such as AWS, Azure, or Google Cloud.
- Experience with modern platform engineering and DevOps practices, including containers, Kubernetes, Infrastructure-as-Code, and cloud-native architectures.
- Familiarity with modern web application architectures
- API design, development, and integration expertise
- AI & LLM Engineering (25%)
- Experience leveraging Large Language Models (LLMs) to solve business problems
- Strong understanding of prompt engineering, prompt management, and GenAI solution design
- Experience working with GenAI developer tools such as: GitHub Copilot, Gemini, Claude
- Familiarity with AI strategy, implementation, and scaling AI-driven solutions
- Data Platform Engineering (25%)
- Strong data engineering experience
- Experience with data pipelines, data stores, orchestration frameworks, and distributed systems
- Understanding of machine learning workflows and AI-enabled applications
- Experience deploying and scaling AI/ML solutions in production environments
- Cloud Architecture, Scale & Security (25%)
- Cloud-native development experience
- Kubernetes and containerized application deployment
- Experience with deployment patterns and scalable system design
- Understanding of secure, enterprise-grade architecture
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