Senior AI Engineer (Agentic Systems & AI Platforms)

Role overview A Senior AI Engineer is needed to design, build, and ship production AI systems, including agentic pipelines, RAG architectures, and cloud-native AI platforms that integrate into real workflows. The role sits at the intersection of agentic AI, workflow automation, and product delivery, focused on systems that continuously improve through feedback rather than research prototypes.

Responsibilities - Design, build, and optimize agentic AI pipelines for automation and workflow intelligence. - Develop and deploy RAG-based systems using vector databases and contextual retrieval. - Implement model orchestration strategies covering prompting, routing, memory, and tools. - Build and operate AI-powered microservices in cloud environments and integrate them into real products, APIs, and workflows. - Continuously improve system performance through prompt engineering, context tuning, evaluation frameworks, and feedback loops. - Deploy and maintain scalable, secure AI services with strong observability, CI/CD pipelines, and infrastructure automation. - Collaborate with product, engineering, and architecture teams, translating business problems into working AI solutions and building demos, prototypes, and PoCs.

Requirements - 5+ years of software engineering experience in production environments. - Strong experience with Python (primary), or with Node.js and TypeScript. - Hands-on experience building agentic AI systems and RAG architectures. - Solid cloud infrastructure experience, preferably on Azure or AWS. - Background in microservices, CI/CD, and production-grade observability. - Bias for execution, comfort with ambiguity, and ability to move from experimentation to production quickly.

Benefits and work setup - Remote position, available as either full-time or contract engagement. - High-ownership, high-autonomy environment with fast iteration and direct work on core AI systems.