Expert AI Engineer
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.
Remote AI Engineer Jobs in Bulgaria
105 AI Engineer jobs in Bulgaria available for remote work from home. Apply for positions such as Expert AI Engineer, Offensive AI Engineer, AI Engineer - Public Sector and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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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 and build LLM-powered autonomous hacking agents capable of performing full-scale offensive security attacks with minimal human intervention. Develop agent architectures, integrate offensive security toolchains, and build evaluation harnesses to measure AI performance.
Architect and deploy production-grade RAG pipelines and agentic workflows to process complex multimodal data for government and military clients. Balance high-level R&D and experimentation with the delivery of scalable, production-ready software on AWS.
The role involves leading the technical direction of AI agents responsible for translating natural language into production-ready applications, focusing on defining patterns for LLM interaction, context maintenance, and multi-step workflow orchestration. This includes owning the technical vision for how agents reason about and generate full-stack applications, driving initiatives that influence the broader AI strategy.
As a Senior Applied AI Engineer, you will develop AI agents that transform natural language into production-ready applications and tackle challenges related to maintaining context across large codebases. You will also collaborate with teams to ensure AI-driven features are efficient and well-monitored in deployment.
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You will own the architecture and implementation of Elixir-based applications while managing autonomous coding-agent workflows to deliver reliable software. The role involves translating market needs into technical specifications and maintaining proactive communication with clients and the team.
Own and improve the client’s Quickbase systems while building a broader internal operations platform, including workflows, automations, integrations, dashboards, and web-based tools. Assess business processes and determine when to improve Quickbase, build custom software, integrate other systems, or apply AI, while protecting sensitive data and documenting key decisions.
Design, build, and deploy scalable features powered by large language models, including prompt pipelines, evaluation frameworks, fine-tuned models, and retrieval systems. Integrate AI capabilities into production systems and APIs, optimizing performance, latency, and cost while collaborating with product and engineering teams.
Provide 24x7 oversight and incident management for AI/ML infrastructure while delivering low-latency support to customers. Manage compute, storage, and network resource pools to ensure SLA compliance and maintain operational documentation.
You will lead an end-to-end AI workstream by translating complex business processes into reliable, reusable AI agents. This involves direct stakeholder engagement, designing technical solutions, and ensuring successful user adoption through rigorous testing and evaluation.
Design and build scalable data pipelines to support machine learning workflows, including feature engineering and real-time data ingestion. Collaborate with cross-functional teams to ensure data quality, monitoring, and efficient model deployment.
Design and implement AI-driven automation solutions for complex lending, underwriting, and document-processing workflows. Integrate AI models with existing enterprise software and data sources to optimize operational efficiency and decision-making.
You will architect and evolve backend systems while leveraging AI-assisted development tools to build scalable APIs and features. Additionally, you will create internal tooling and engineering systems to improve velocity and code quality across the organization.
Build and maintain batch and real-time pipelines for structured and unstructured data, and support storage, access, and AI-ready data foundations such as embeddings and vector indexing. Collaborate with data and AI teams to integrate models into workflows, apply basic governance and security practices, and translate requirements into practical data solutions.
The Senior AI Test Engineer will be responsible for designing and executing comprehensive test strategies for AI-driven systems. They will ensure the reliability, accuracy, and performance of AI models through rigorous testing protocols.
The AI agent engineer will design, build, and manage a team of AI agents to optimize company operations and improve customer service. They will collaborate with department leads to identify AI integration opportunities and evaluate the performance of various models and tools.
Architect and develop production-grade autonomous agents and orchestration frameworks using tools like LangChain and AutoGen. Lead technical implementation across multiple squads to ensure standardized, scalable, and high-performance AI solutions.
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You will architect and build multi-agent AI systems and RAG pipelines while owning the full-stack development lifecycle from UI to cloud deployment. You will collaborate with product owners to translate requirements into production-ready AI features with a focus on performance, cost, and reliability.
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.
Design, develop, and deploy production-ready Agentic AI applications and scalable backend services. Manage API integrations, data transformation pipelines, and service orchestration while ensuring application reliability and performance.
Design and build scalable systems, tooling, and data processing pipelines to improve AI delivery and evaluation. Lead the end-to-end execution of data collection projects for frontier AI labs to improve advanced models.
Build a high-performance AI platform and backend in Rust to power an AI-native trading experience. Design robust APIs and safe action infrastructure for trading workflows, including orchestration of models and tools.
Build and maintain an MVP evaluation harness including golden tasks and scorecard metrics. Integrate quality evaluations into the CI pipeline to gate releases and prevent regressions.
Train and evaluate next-generation Large Language Models by auditing model logic, code, and reasoning. Provide high-quality human feedback to refine RLHF frameworks and benchmark model performance.
You will write maintainable, scalable, and performant backend code primarily in Go, Java, and Python, while building high-volume analytics systems. Additionally, you will design and build APIs specific to customer workflows and contribute to the development of in-house AI agents.
You will write maintainable, scalable, and performant code across the stack primarily in Typescript and React, and design and build APIs specific to customer workflows. Additionally, you will collaborate with product and design teams to enhance product offerings and contribute to architectural decisions.
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Provide oversight to frontline NOC teams to ensure 24x7 service uptime and rapid incident response for AI cloud infrastructure. Manage compute, storage, and network resource pools while driving automation and documentation efforts to improve reliability.
Develop and maintain scalable Python applications, backend services, and production-ready Agentic AI solutions, including autonomous agents and multi-agent workflows. Integrate LLMs, APIs, tool and function calling, and RAG where applicable, while supporting testing, deployment, and optimization.
You will serve as the primary technical architect for large-scale AI and HPC customer initiatives, bridging the gap between business objectives and hardware execution. Responsibilities include designing GPU supercomputing clusters, generating detailed bills of materials, and guiding customers through successful deployments.
You will serve as the lead technical architect, designing the platform's infrastructure, data layers, and AI agent workflows while guiding a distributed team of engineers. You will be hands-on in building core framework skeletons and defining technical standards for production-grade AI systems.
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