
JODAYN
Riyadh, Saudi ArabiaPosted 4 months ago
Apply link checked yesterday
Jodayn is seeking a highly skilled Senior AI Product Engineer to lead the design, development, and deployment of enterprise-grade artificial intelligence solutions and intelligent automation platforms. The successful candidate will play a critical role in developing scalable AI-powered products and reusable enterprise AI services that support digital transformation, governance automation, proposal evaluation, intelligent document processing, and enterprise workflow optimisation. This role requires a strong engineering mindset combined with hands-on experience in modern AI frameworks, large language model integration, AI orchestration, backend engineering, and enterprise solution development. The ideal candidate must be capable of independently designing and delivering production-ready AI systems in fast-paced enterprise environments.
Lead design, development, and deployment of enterprise-grade AI solutions and intelligent automation platforms. Build modular and reusable AI services and APIs. Develop AI-powered workflow automation systems and orchestrations. Design scalable backend architectures for AI workloads. Build autonomous AI agents and multi-agent orchestration workflows. Integrate AI systems with external tools, APIs, and enterprise applications. Integrate and optimize large language model services (Claude, OpenAI, open-source models). Develop prompt orchestration pipelines and retrieval-augmented generation architectures. Implement vector database integration and semantic search. Integrate AI platforms with enterprise systems, collaboration tools, and document repositories. Develop secure API integration patterns and authentication/identity integration. Build AI-enabled enterprise workflow capabilities. Develop intelligent proposal generation and evaluation systems; implement AI-assisted scoring and governance automation. Deploy AI applications across cloud, hybrid, and on-premise environments; implement logging, observability, monitoring, and diagnostics; support containerisation and deployment automation; optimize infrastructure scalability and cost efficiency.
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