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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, AIOps & Infrastructure at Eloquent AI - **Company:** Eloquent AI - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Automated Storage and Retrieval Systems, Microsoft Azure, Cloud Computing, Distributed Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Software Engineering, AI Infrastructure, Data Logging, Google Cloud, System Availability, Delivery Pipeline, Large Language Models, Build Management, Kubernetes, Machine Learning Operations, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/ai-engineer-aiops-infrastructure-eloquent-ai-8142705 ## About the Role * 5+ years of experience in software engineering, MLOps, or infrastructure development. * Strong expertise in Kubernetes and experience managing containerized ML workloads. * Deep understanding of cloud platforms (AWS, GCP, Azure) and distributed computing. * Proficiency in Python, with experience developing services for ML/AI applications. * Experience with ML model deployment pipelines, including model serving, inference optimization, and monitoring. * Familiarity with vector databases, retrieval systems, and RAG architectures is a plus. * Strong problem-solving skills and the ability to work in a high-scale, production-focused AI environment. Bonus Points If… * You have experience with LLMOps, fine-tuning, and deploying large-scale AI models. * You've worked with GPU workload optimization, ML model parallelization, or distributed training strategies. * You have experience building infrastructure for AI-powered applications. * You've contributed to open-source MLOps tools or AI infrastructure projects. * You thrive in a fast-moving startup environment and enjoy solving complex technical challenges. ## Description As a Senior Software Engineer, AIOps & Infrastructure at Eloquent AI, you will be responsible for designing, building, and optimizing scalable, high-performance AI infrastructure to support the deployment and operation of our enterprise AI agents. Your work will enable machine learning engineers and AI teams to train, fine-tune, and deploy LLMs efficiently while ensuring stability, observability, and performance at scale. You'll play a key role in automating LLMOps and MLOps workflows, optimizing GPU workloads, and ensuring resilient, production-ready AI systems. This role requires deep expertise in cloud infrastructure, Kubernetes, and LLM and ML deployment pipelines. If you're passionate about scalable AI systems and optimizing ML models for real-world applications, this is your opportunity to work at the frontier of LLMOps. You will: * Design and build scalable ML infrastructure for deploying and maintaining AI agents in production. * Automate LLMOps and MLOps workflows, ensuring seamless model training, fine-tuning, deployment, and monitoring. * Optimize GPU and cloud compute workloads, improving efficiency and reducing latency for large-scale AI systems. * Develop Kubernetes-based solutions, including custom operators for ML model orchestration. * Improve system observability and reliability, implementing logging, monitoring, and performance tracking for AI models. * Work with ML and engineering teams to streamline data pipelines, model serving, and inference optimizations. * Ensure security, compliance, and reliability in AI infrastructure, maintaining high availability and scalability. * Participate in on-call rotations, ensuring 24/7 reliability of critical AI systems. ## Related Videos - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Crypto-secure Data Management with In-Database Blockchain](https://www.wearedevelopers.com/videos/632-crypto-secure-data-management-with-in-database-blockchain) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [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) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)