Senior AI Engineer

Senior AI EngineerRun & Maintain AI ProductsWrite Python code and leverage cloud platforms like Azure, Google Cloud, and OpenShift for deploying and modeling a variety of machine learning solutions.Support and maintain in-house generative AI systems, such as a custom GPT-based solution.Build and upkeep AI APIs and backend services powering our custom AI applications.Use tools like Azure OpenAI, vector databases, LangChain, and related libraries to develop and deploy specialized GenAI applications.Optimize Performance & ScalabilityQuickly respond to service incidents and requests to guarantee high availability and reliability of our AI products in production.Profile, fine-tune, and optimize both machine learning models and backend infrastructure to meet SLA targets.Research and propose new architectural patterns or technologies that could enhance the performance of existing offerings.Automate infrastructure setup (Infrastructure as Code) and CI/CD pipelines for AI workloads.What You’ll BringMust-HaveDegree (Bachelor’s) in Computer Science, Software Engineering, Information Systems, or related discipline.3–5 years of practical experience in data science or AI engineering, especially using cloud-based services.Advanced proficiency in Python, with the ability to adapt to other languages when needed.Hands-on experience with LangChain and familiarity with Azure OpenAI (or comparable platforms).Proven ability to build retrieval-augmented generation (RAG) pipelines from scratch using LangChain or similar libraries.Strong version control skills, especially with Git (GitHub and GitOps).Experience building AI-based APIs and deploying them via an AI marketplace.Excellent analytical and problem-solving skills—able to dig into complex data issues under tight SLAs.Strong communication skills, able to bridge the gap between technical teams, business stakeholders, and senior leadership.A proactive, continuous-improvement mindset; capable of turning vague requirements into actionable tasks.Big AdvantageMaster’s degree in a relevant field (Computer Science, Software Engineering, Information Systems, etc.).Experience with containerization tools such as Docker and orchestration platforms like Kubernetes.Familiarity with Azure’s data science ecosystem and related services.Knowledge of Google Cloud Platform (GCP), OpenShift, or SAP technologies.