Senior AI Platform Engineer
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Job Location:
Charlotte, VT - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Job Summary:
We are seeking a high-caliber Senior AI Platform Engineer to drive the design and development of our enterprise-grade AI platform. This role is at the intersection of full-stack engineering and advanced Generative AI. You will be responsible for building scalable secure and production-ready capabilities that support both SaaS and federated deployment models. 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
We are seeking a high-caliber Senior AI Platform Engineer to drive the design and development of our enterprise-grade AI platform. This role is at the intersection of full-stack engineering and advanced Generative AI. You will be responsible for building scalable secure and production-ready capabilities that support both SaaS and federated deployment models. 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
