About the role
We are seeking an LLM Deployment Engineer to drive the adoption of AI-powered automation across the organization. In this role, you will deploy and scale LLMs to streamline business processes and assist engineering R&D.
You'll work at the intersection of ML, software infrastructure engineering, and enterprise systems, by developing integration and automation solutions that enable teams across the organization to operate more efficiently.
What You´ll Do
· Deploy and maintain open-weights LLMs on cloud and local cluster.
· Scale deployments to serve a large number of users within the organization.
· Be up-to-date with new model releases, to keep our deployment state of the art.
· Connect LLMs to specific use cases, helping users across the organization to automate their work routine.
· Analyze the effectiveness of models on automation tasks.
· Embed security and privacy in the automation pipeline, to safeguard sensitive content.
Requirements
What You’ll Need
· 3+ years of professional experience in software engineering
· Experience working with LLM APIs, both open-weight and proprietary
· Familiarity with LLM applications, including tools, retrieval-augmented generation (RAG) and routing
· Experience with CI/CD pipelines, infrastructure as code, and modern software delivery practices
· Understanding of security and privacy considerations in enterprise environments
· Strong problem-solving skills and the ability to collaborate effectively across technical and non-technical teams
Nice to have
· Knowledge of Model Context Protocol (MCP) or similar interoperability standards
· Experience with AI governance, observability, or operational monitoring
· Proficiency with cloud platforms (AWS, GCP, or Azure), and high-performance computing environments (Kubernetes, SLURM).
· Experience in evaluating ML models.
Who You Are
You thrive in fast-paced environments where ambiguity is part of the challenge, and you can turn it into defined goals. You take ownership seriously and move things forward without waiting for perfect conditions. You know how to balance structure with flexibility without losing focus. Above all, you measure success by outcomes and take pride in getting things done.
Summary
Deploy and scale open-weights LLMs on cloud and local clusters, connecting them to business use cases while embedding security and privacy. Requires 3+ years of software engineering experience, LLM API and RAG familiarity, CI/CD, infrastructure as code, and cross-functional collaboration.
Responsibilities
Deploy and maintain open-weights LLMs on cloud and local clusters; scale deployments; track model releases; connect LLMs to use cases; analyze model effectiveness; embed security and privacy in automation pipelines
Qualifications
3+ years professional software engineering experience; LLM API, application, RAG, and routing experience; CI/CD and infrastructure-as-code experience; security and privacy understanding; problem-solving and cross-team collaboration
Experience requirements
3+ years professional software engineering; experience with LLM APIs (open-weight and proprietary), LLM applications, tools, RAG, and routing; CI/CD pipelines, infrastructure as code, and modern software delivery; security and privacy in enterprise environments; problem-solving and collaboration