Overview
On Site
Contract - W2
Skills
Expect
Backend Development
Java
Spring Framework
RESTful
JPA
Hibernate
Relational Databases
PostgreSQL
MySQL
NoSQL
React.js
AngularJS
Vue.js
HTML5
Cascading Style Sheets
JavaScript
TypeScript
Scalability
Version Control
Git
Continuous Integration
Continuous Delivery
Automated Testing
Agile
Streaming
Apache Kafka
Orchestration
Docker
Kubernetes
Cloud Computing
UI
Microservices
Conflict Resolution
Problem Solving
Communication
Collaboration
DevOps
Quality Assurance
Articulate
Vector Databases
Semantic Search
Video
Evaluation
Prompt Engineering
Testing
Workflow
SDK
Artificial Intelligence
Job Details
Title: AI Engineer
Location: Charlotte, NC (Onsite)
Duration: Initial contract till year end, we expect to extend 6months+
Role Description
Must-have skills & experience
Location: Charlotte, NC (Onsite)
Duration: Initial contract till year end, we expect to extend 6months+
Role Description
Must-have skills & experience
- 3-6 years of hands-on experience building full stack applications using Java and the Spring Boot framework (or equivalent) in a production environment.
- Experience working in a large enterprise or complex organization (multiple teams, services, stakeholders).
- Solid backend development skills: Java 8+, Spring Boot, RESTful APIs, data access (JPA/Hibernate), relational databases (e.g., PostgreSQL, MySQL) and familiarity with NoSQL as a plus.
- Frontend experience: delivered client side UI using frameworks like React (strongly preferred) or Angular/Vue, with good working knowledge of HTML5, CSS, JavaScript/TypeScript.
- Hands-on experience with modern AI workflows: developing agents, working with LLMs, integrating AI capabilities into applications (e.g., prompt engineering, model orchestration)
- Experience taking an AI-centric systems into production: build, deploy, monitor, troubleshoot live services, handle performance, scalability, stability.
- Familiarity with enterprise-grade practices: version control (Git), CI/CD pipelines, automated testing (unit, integration), code reviews, agile methodologies.
- Experience building event-driven or streaming systems (Kafka, Reactor, etc.).
- Experience with containerization and orchestration (Docker, Kubernetes) or cloud deployments.
- Hands-on developing front-end/back-end interactions in the context of AI workflows (UI for model output, integrations).
- Understanding of architecture in enterprise settings: microservices or modular architectures, ability to work within a larger ecosystem of services, dependencies, security and operations concerns.
- Excellent problem-solving skills, able to diagnose issues in production systems and propose solutions.
- Good communication skills: work across teams (DevOps, QA, product, architecture) and clearly articulate technical trade-offs.
- Implementing retrieval-augmented generation (RAG) systems with vector databases and semantic search
- Building multi-modal AI systems integrating text, image, audio, or video processing
- Experience with AI safety techniques including constitutional AI, red teaming, and alignment evaluation
- Building AI agent frameworks with tool use, planning, and memory capabilities
- Implementing human-in-the-loop systems for continuous model improvement and feedback collection
- Knowledge of AI governance, model versioning, and experiment tracking in production environments
- Building robust prompt engineering frameworks with versioning and A/B
- testing capabilities
- Experience with LLM observability, monitoring token usage, latency, and quality metrics in production
- Implementing guardrails and content filtering for responsible AI deployment
- Familiarity with Google's agent/workflow tooling (e.g., Google Actions SDK or other Google-AI tooling).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.