Junior / Middle AI Engineer (Agentic AI / LLM)

New

DCV TechnologiesAgentic AI

Remote – Europe, Must be available for US–Europe time zone overlap, with availability until approximately 18:00–19:00 CET.Full-TimeMiddle

Salary not disclosed

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Job Details

Have 2+ years of hands-on experience in Python software engineering, backend development, or applied AI/LLM engineering.
Have practical experience building LLM-powered applications, RAG pipelines, or AI agent workflows.
Be familiar with agentic AI frameworks and technologies such as LangChain, LlamaIndex, and LLM APIs including OpenAI, Anthropic, or Mosaic AI.
Have Python and REST API development experience, including FastAPI or Flask.
Understand JSON schemas, API integrations, asynchronous programming, and error handling.
Be familiar with Git and collaborative software development workflows.
Understand vector databases, embeddings, semantic search, and retrieval techniques.
Have basic experience with SQL and cloud or data platforms such as Databricks, AWS, or Azure.
Be available for US–Europe time-zone overlap, typically until 18:00–19:00 CET.
Production deployment experience with LLM-powered applications is a plus.
Familiarity with LLM evaluation, observability, tracing, monitoring, AI safety, guardrails, structured outputs, or hallucination mitigation is a plus.
Experience with Docker, CI/CD, cloud deployment, multi-agent architectures, or orchestration patterns is a plus.

Build, configure, and maintain AI agent workflows, prompt chains, and tool/function-calling integrations within the AgentQ ecosystem.
Develop REST API connectors, backend services, and data retrieval pipelines connecting enterprise systems, external APIs, and agent workflows.
Implement and optimize RAG pipelines, embeddings, and integrations with vector databases and enterprise data sources.
Design automated test suites, benchmark datasets, and evaluation frameworks for agent accuracy, response quality, latency, and guardrail compliance.
Troubleshoot agent behavior, monitor production executions, and improve prompts, retrieval strategies, and fallback mechanisms.
Maintain technical documentation covering agent architectures, API interfaces, integrations, testing processes, and operational runbooks.
Collaborate with senior AI engineers and backend teams on reliable AI automation capabilities and production deployments.

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