AI Platform Engineer

About the Company: 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.

About the Role: This role involves key responsibilities that include the design, development, and delivery of enterprise-grade AI platform capabilities.

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.

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.

Required Skills:

• 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.

Pay range and compensation package: [Insert pay range or salary or compensation details here]

Equal Opportunity Statement: We are committed to diversity and inclusivity in our hiring practices.