Role : AI Engineers
Location : Charlotte NC (Onsite)
Hire type : Contract
The ideal candidate is an expert in Python and React, with a deep understanding of Agentic workflows, MCP-based services, and RAG architectures.
Key Responsibilities:
AI Platform Architecture: Design, develop, and deliver enterprise-grade AI platform capabilities that support diverse deployment models, including SaaS and federated environments.
Agentic Workflows: Build and integrate Model Context Protocol (MCP) based agentic services, designing complex workflows and reusable application components for widespread internal use.
Full-Stack Development: Develop and maintain scalable, high-performance backends using Python and responsive, modern frontends using React.
Advanced AI Implementation: Lead the development of RAG-based systems, autonomous AI agents, and diverse data-driven use cases to solve complex business problems.
Security & DevOps: Integrate robust security protocols, comprehensive logging, and automated CI/CD pipelines to ensure platform stability and compliance.
Cross-Functional Leadership: Collaborate with product managers, data scientists, and security teams to deliver seamless, production-ready AI solutions from concept to deployment.
Must-Have Qualifications:
Technical Proficiency: Strong expertise in Python (backend) and React (frontend) for building large-scale web applications.
AI Specialization: Proven experience building RAG systems and orchestrating AI Agents.
Protocol Knowledge: Practical experience with MCP (Model Context Protocol) and building component-based architectures.
Enterprise Standards: Deep understanding of enterprise-grade security, logging, and infrastructure automation (CI/CD).
Deployment Experience: Hands-on experience delivering and managing capabilities in SaaS and federated environments.
Problem Solving: Ability to translate complex data-driven requirements into scalable software solutions.
Good-to-Have:
Experience with containerization (Docker, Kubernetes).
Knowledge of vector databases (e.g., Pinecone, Milvus) and LLM observability tools.
Experience working in a fast-paced IT services or product-led organization
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