Principal MLOps Engineer
Location: Remote from Spain (Spanish employment contract)
We are looking for Principal MLOps Engineer to support the development of AI-driven solutions in General Digital Marketing team of a Leading Agricultural Company. The engineers will work on projects involving generative AI, intelligent agents, and process automation, integrating with large-scale enterprise systems. The current goals are to create two LLM agents, that are responsible for producing marketing Campaigns materials – campaign information, images, presentations, slogans, etc.
Requirements:
- Proven experience in developing and deploying generative AI or LLM-based applications - Participate on the architectural design of conversational solutions. - Strong prompt proficiency with LLMs such as OpenAI, Azure OpenAI, Claude, or LLaMA - Hands-on experience with LangChain, LangGraph. Other frameworks are also valued. - Solid understanding of semantic search, RAG pipelines, and vector embeddings - AWS experience with ECR, ECS/Fargate and dockerization. - Design/Deploy MCP servers. - Background in API/microservices development - Ability to work with enterprise-grade architectures and process automation tools - English: at least B2 level.
Will be a plus:
- Experience with n8n, Semantic Kernel, Copilot Studio, - Experience with MLOps, model optimization, and cloud deployments (especially AWS) - Previous experience with digital marketing life cycle. - SQL proficiency - Expertise using Claude Code, GitHub copilot and similar tools as part of their daily tooling, working routines
Responsibilities:
- Lead the development of LLM-based intelligent agents - Prepare system architecture, agree system design with stakeholders - Contextualization of the company data. - Implement Retrieval-Augmented Generation (RAG) systems - Integrate LLMs with varius different data sources - Leverage tools like LangChain, LangGraph, Semantic Kernel, and Copilot Studio to build semantic workflows - Automate internal processes using n8n - Collaborate with cross-functional teams including DevOps, backend, and business stakeholders - Contribute to best practices for AI deployment, prompt engineering, and model evaluation