AI Platform Engineer
Listed on 2026-06-06
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IT/Tech
AI Engineer
About the Company
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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
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This role involves key responsibilities that include the design, development, and delivery of enterprise-grade AI platform capabilities.
Responsibilities
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- AI Platform Architecture
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Design, develop, and deliver enterprise-grade AI platform capabilities that support diverse deployment models, including SaaS and federated environments. - Agentic Workflows
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Build and integrate Model Context Protocol (MCP) based agentic services, designing complex workflows and reusable application components for widespread internal use. - Full-Stack Development
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Develop and maintain scalable, high-performance backends using Python and responsive, modern frontends using React. - Advanced AI Implementation
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Lead the development of RAG-based systems, autonomous AI agents, and diverse data-driven use cases to solve complex business problems. - Security & Dev Ops
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Integrate robust security protocols, comprehensive logging, and automated CI/CD pipelines to ensure platform stability and compliance. - Cross-Functional Leadership
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Collaborate with product managers, data scientists, and security teams to deliver seamless, production-ready AI solutions from concept to deployment.
Qualifications
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- Technical Proficiency
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Strong expertise in Python (backend) and React (frontend) for building large-scale web applications. - AI Specialization
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Proven experience building RAG systems and orchestrating AI Agents. - Protocol Knowledge
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Practical experience with MCP (Model Context Protocol) and building component-based architectures. - Enterprise Standards
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Deep understanding of enterprise-grade security, logging, and infrastructure automation (CI/CD). - Deployment Experience
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Hands-on experience delivering and managing capabilities in SaaS and federated environments. - Problem Solving
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Ability to translate complex data-driven requirements into scalable software solutions.
Required Skills
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- 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
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We are committed to diversity and inclusivity in our hiring practices.
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