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Flatrock

Dear recruiters there is no need to edit this.

Agentic AI Engineer

AI EngineerMachine Learning EngineerFull TimeRemoteMid Level

Location

Bulgaria

Posted

97 days ago

Salary

€1.2K / year

Seniority

Mid Level

No structured requirement data.

Job Description

Agentic AI Engineer

Flatrock

Role Description - Design and build agentic AI systems, including autonomous agents, multi-agent orchestration, workflow state machines, and tool-using agents. - Develop LLM-driven agents capable of reasoning, planning, retrieval (RAG), and task execution across enterprise systems. - Build and maintain AI-powered automation workflows using platforms like n8n and Make to orchestrate business processes and cross-application integrations. - Integrate agents with APIs, CRM/ERP systems, collaboration tools, databases, and payment platforms using tool/function calling, MCP, and A2A patterns. - Implement robust execution logic (validation, retries, rate limits, fallbacks, error handling) to ensure reliability and scalability. - Design and manage RAG pipelines using embeddings, vector databases, chunking, and reranking strategies. - Establish safety guardrails, access controls, and human-in-the-loop workflows for high-risk actions. - Build evaluation, observability, and tracing pipelines to monitor performance, cost, latency, and reliability. - Deploy and operate agent services in cloud environments (AWS, Azure, or GCP) using Docker, Kubernetes, Terraform, and CI/CD. - Monitor production systems, troubleshoot issues, and continuously improve agent performance and policies. - Prototype and benchmark emerging agentic AI frameworks and models. - Create technical documentation and communicate AI solutions effectively to cross-functional stakeholders. Qualifications - Bachelor’s or Master’s degree in Computer Science, AI, Engineering, or related field. - 3+ years of software engineering experience (Python and/or TypeScript). - 1+ year building LLM-powered or agentic AI systems in production or near-production environments. - Experience with agent frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel). - Hands-on experience with automation/orchestration tools (e.g., n8n, Make) in production settings. - Strong understanding of LLMs, embeddings, prompt engineering, structured outputs, and tool calling. - Experience designing REST APIs, microservices, and backend systems. - Familiarity with vector databases and RAG architectures. - Experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and infrastructure-as-code tools. - Strong system design, debugging, and communication skills. Requirements - Experience with MCP, A2A, or advanced agent communication patterns. - Advanced experience with n8n (custom nodes, self-hosting) or Make (complex scenarios). - Experience combining LLMs with workflow engines for document processing, reporting, chatbots, or decision support. - Familiarity with AI evaluation and observability tools (e.g., LangSmith, OpenAI Evals, Weights & Biases). - Experience with multi-agent systems, planning algorithms, RL, fine-tuning, or RLHF. - Knowledge of CI/CD pipelines and security best practices. - Experience in regulated industries (e.g., healthcare, finance, defense). - Relevant cloud or ML certifications. Company Description Dear recruiters there is no need to edit this.

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