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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Ai Back End Engineer (Llm Specialist) - **Company:** Talanto - **Location:** Huelva, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Computing Security, Program Optimization, Continuous Integration, DevOps, Distributed Systems, Github, Infrastructure as a Service (IaaS), Python (Programming Language), Platform as a Service (PAAS), Software Architecture, Cloud Services, Prometheus, Chatbots, Delivery Pipeline, Large Language Models, Grafana, Prompt Engineering, Backend, Fastapi, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Terraform, GPT, Serverless Computing, Jenkins, Microservices - **Published:** August 1, 2026 - **Apply:** https://www.buscojobs.com.es/ai-back-end-engineer-llm-specialist-en-huelva-ID-364874074 ## About the Role 5+ years of experience designing and implementing cloud solutions in AWS (Azure is a plus) . Proven background in building solutions involving IaaS, PaaS, Serverless, and distributed architectures. Advanced knowledge of Kubernetes, microservices, and IaC (Terraform). Hands-on experience with Machine Learning pipelines, MLOps, and LLM-based solutions (Chatbots, RAG). Strong experience developing in Python, including FastAPI. Experience with observability tools (Prometheus, Grafana, ELK, OpenTelemetry) and CI/CD/DevOps practices. High level of English (C1 or equivalent) . Nice to have Experience with Cloud Security and compliance. Familiarity with cloud cost-optimization tools and automation frameworks. ## Description Senior AI Platform Backend Engineer (LLM): Designing and implementing cloud infrastructure and backend architecture for AI Verification and Az ChatGPT Services with an accent on MLOps, LLM-as-a-judge production services, and high-load RAG solutions. Focus on optimizing model latency, prompt engineering, and evaluating agent-based solutions for AI-generated content validation.Location:Hybrid in Barcelona, Spainwith remote-work options.CompanyNEORIS, now part of EPAM, is a Digital Accelerator with over 20 years of experience, fostering a multicultural and startup-driven culture to create high-impact solutions for clients globally.What you will doDesign, implement, and manage cloud infrastructure on AWS using Infrastructure as Code (IaC) tools like Terraform.Maintain and improve CI/CD pipelines using tools such as GitHub Actions, AWS CodePipeline, Jenkins, or ArgoCD.Develop backend architecture for AI Verification and Az ChatGPT Services using Python and FastAPI.Develop and maintain LLM-as-a-judge production services for validating AI-generated content, optimizing model latency.Design, build, and maintain high-load RAG solutions including ingestion and retrieval services.Perform prompt engineering using techniques like Chain-of-Thought across multiple LLMs.Requirements5+ years of experience designing and implementing cloud solutions in AWS (Azure is a plus).Proven background in building solutions involving IaaS, PaaS, Serverless, and distributed architectures.Advanced knowledge of Kubernetes, microservices, and IaC (Terraform).Hands-on experience with Machine Learning pipelines, MLOps, and LLM-based solutions (Chatbots, RAG).Strong experience developing in Python, including FastAPI.Experience with observability tools (Prometheus, Grafana, ELK, OpenTelemetry) and CI/CD/DevOps practices.High level of English (C1 or equivalent).Nice to haveExperience with Cloud Security and compliance.Familiarity with cloud cost-optimization tools and automation frameworks.Culture & BenefitsPermanent contract with a competitive salary.Flexible work model with remote-work options.Personalized career plan and continuous training (certifications, English, etc.).Participation in stable projects with strong technical components.Flexible schedule with focus on work-life balance.Social benefits tailored to your needs.#J-*****-Ljbffr ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) ## Related Articles - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [The 7 Most Popular Backend Frameworks for Developers](https://www.wearedevelopers.com/magazine/403-the-7-most-popular-backend-frameworks-for-developers)