VPP-94 - LLM Ops Engineer

• Design and maintain scalable infrastructure for LLM and Generative AI applications.
• Build and manage LLMOps/MLOps pipelines for model, prompt, and application deployment.
• Develop and maintain CI/CD pipelines for AI/ML workloads.
• Deploy and manage LLM inference services and model-serving infrastructure.
• Implement monitoring and observability for model performance, latency, availability, errors, and resource utilization.
• Monitor and optimize LLM costs, token consumption, latency, and inference performance.
• Establish processes for model, prompt, dataset, and configuration versioning.
• Automate deployment, testing, rollback, and release processes.
• Build infrastructure using Infrastructure as Code (IaC) and cloud-native technologies.
• Implement appropriate security, access controls, secrets management, and data protection practices.
• Troubleshoot production issues and improve system reliability and scalability.
• Establish best practices for LLM evaluation, observability, and production monitoring.
• Continuously evaluate emerging LLM infrastructure, serving technologies, and AI platform capabilities.

• 7+ years of experience in DevOps, MLOps, ML Engineering, Platform Engineering, or a related field.
• 4+ years of hands-on experience supporting LLM/Generative AI workloads in production.
• Strong experience with at least one major cloud platform: AWS, Azure, or GCP.
• Strong knowledge of Docker and Kubernetes.
• Experience building and maintaining CI/CD pipelines.
• Strong Python and scripting skills.
• Experience with Infrastructure as Code, preferably Terraform.
• Experience with ML/LLM deployment and model-serving frameworks.
• Understanding of LLM architectures, inference workflows, embeddings, RAG, and vector databases.
• Experience with observability and monitoring tools.
• Strong understanding of APIs, microservices, networking, and distributed systems.
• Experience with Git and modern software development practices.
• Strong troubleshooting and problem-solving skills.

• Experience with platforms and tools such as MLflow, Kubeflow, LangChain, LangGraph, Ray, vLLM, or similar technologies.
• Experience with LLM APIs such as OpenAI, Anthropic, Google, or Azure OpenAI.
• Experience implementing LLM evaluation and quality monitoring frameworks.

Vekend is a people-first organization focused on developing thoughtful products and services that create meaningful impact for our customers and communities. We are committed to fostering a collaborative, respectful, and inclusive work environment where employees are empowered to take ownership of their work, contribute ideas, and grow professionally. We strive to support flexibility and work-life balance while maintaining high standards of performance and accountability.

For all locations, the good-faith, reasonable annualized full-time compensation for this role will be determined based on competitive market data and may vary depending on geographic location, job-related knowledge, skills, experience, education, and other business considerations. Specific compensation details will be discussed during the interview process.,Vekend offers a comprehensive benefits and wellness package designed to support employees’ overall well-being, financial security, and professional growth. Eligibility and coverage are subject to the terms of the applicable benefit plans and company policies. Eligible employees have access to medical, dental, and vision insurance with company contributions toward premiums, a 401(k) retirement plan with company matching, and Paid Time Off that begins accruing on the first day of employment. We also support flexible work arrangements and opportunities for professional growth. Benefits eligibility, coverage, and company contributions are subject to the terms of the applicable plan documents and may be modified at the company’s discretion.