18 AI Engineer jobs in Bulgaria available for remote work from home. Apply for positions such as Staff Software Engineer - AI Applied Engineering, Agentic AI Engineer, Senior AI Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will design and build end-to-end AI agent features, including RAG and tool-use capabilities, while managing production performance and reliability. Additionally, you will define evaluation strategies for AI outputs and drive model iteration to ensure high-quality, cost-effective system performance.
Design and build agentic AI systems, including autonomous agents, multi-agent orchestration, and workflow state machines. Integrate agents with enterprise systems and build automation workflows to orchestrate business processes.
Own and drive the quality, reliability, and evolution of production AI systems, including the delivery of major AI features. Design and orchestrate agentic, tool-using AI workflows and manage prompt engineering and experimentation pipelines.
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Lead the design and development of agentic AI systems across engineering productivity, internal company intelligence, and customer-facing features. Establish technical standards for AI deployment on GCP and mentor the engineering team in agentic systems expertise.
Lead the design, development, and deployment of advanced AI systems and scalable LLM-driven applications. Act as a technical authority for clients while mentoring peers and contributing to presales engineering solutions.
Design, build, and deploy production-ready AI and machine learning systems, including end-to-end pipelines and microservices. Collaborate with cross-functional teams to integrate LLMs and RAG architectures into scalable healthcare applications.
Design and build agentic AI systems, including autonomous agents, multi-agent orchestration, and workflow state machines. Integrate agents with enterprise systems and manage RAG pipelines while ensuring reliability, scalability, and safety guardrails.
You will build and evolve the agent harness by implementing hooks, permission gates, and context compaction to ensure reliable task completion. Additionally, you will architect planner/executor/evaluator pipelines and manage agent memory to support long-horizon, multi-session execution.
Design, develop, and maintain full-stack application features and services with a focus on AI-powered product experiences. Collaborate with cross-functional teams to ensure system reliability, scalability, and high-performance delivery.
You will own, build, and scale your own startup in the Applied AI sector while receiving intensive coaching and support. You will iterate your product to achieve product-market fit and build essential business functions like sales and marketing.
The engineer will own the inference backbone for QVAC's local AI stack, focusing on the C++ systems layer to ensure models run fast, reliably, and predictably on user hardware. Responsibilities include porting and enhancing inference engines like llama.cpp and ONNX to run efficiently on edge devices, focusing on runtime stability and performance.
Design and build a greenfield analytical data platform on GCP to power internal and customer-facing AI agents. This includes constructing ELT/CDC pipelines, managing orchestration, and developing the retrieval layer for RAG systems.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
We watch for new "AI Engineer" jobs and email you the matches. Free. Unsubscribe in one click.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
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