AI Engineers (Python and React)

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