About Qualifyze
Founded in 2019, Qualifyze is a leading company in supply chain compliance management in the Life Sciences industry, trusted by over 1,500 pharmaceutical and healthcare companies globally. Our digital suite of solutions connects manufacturers, suppliers, and a global network of more than 250 auditors and quality experts. We are looking for an AI Engineer to join our Engineering team.
Responsibilities
•Design, develop and deploy production-ready LLM applications, including RAG pipelines, agents and workflow automation.
•Evaluate and select suitable models, frameworks and providers (e.g. OpenAI, Anthropic, Mistral and open-source alternatives) based on the requirements of each use case.
•Develop evaluation processes and benchmarks to measure AI quality, reliability and potential regressions before and after release.
•Design and manage cloud infrastructure for AI workloads using platforms such as AWS, Azure or GCP and Infrastructure as Code.
•Build and maintain CI/CD pipelines for models, prompts and AI services, including automated testing, controlled releases and rollback processes.
•Deploy and scale AI services using containers and orchestration tools such as Docker, Kubernetes or equivalent managed solutions.
•Implement monitoring and observability for AI systems, covering tracing, latency, output quality, drift and potential failure points.
•Establish usage controls and optimise costs through model selection, caching and batching.
•Investigate and resolve production issues across the AI stack.
•Keep up to date with developments in AI and identify techniques and tools that can bring practical value.
Requirements
•4+ years of experience in software engineering, ML engineering or MLOps/platform engineering, including 2+ years building and deploying LLM-based systems in production.
•Strong Python skills and experience developing production APIs and backend services.
•Practical experience with LLM solutions (e.g. OpenAI, Anthropic, Mistral or similar) and techniques such as RAG, embeddings, vector databases and agent orchestration.
•Experience with cloud platforms such as AWS or GCP and their AI services (e.g. Bedrock, SageMaker or Vertex AI).
•Practical experience with Docker, Kubernetes or equivalent technologies, CI/CD and Infrastructure as Code (e.g. Terraform or similar).
•Experience monitoring and operating AI or ML systems in production.
•Ability to communicate technical decisions clearly to engineering teams and business stakeholders.
•A structured and pragmatic approach to problem-solving, with a sense of ownership.
Nice to have
•Experience in regulated industries such as pharma, life sciences, healthcare or fintech.
•Familiarity with LLM evaluation tools and LLMOps platforms (e.g. Langfuse or MLflow).
•Knowledge of AI governance, regulatory frameworks and IT security standards (e.g. EU AI Act, ISO 42001 and ISO 27001).
•Experience developing internal tools or supporting developer enablement initiatives.
•Experience with agentic coding.
Conditions
•The expected salary range is around 50,000 – 60,000 € per year, centered around the median. Final compensation will depend on experience and performance during the process, with some flexibility within the range.
•Competitive, annually reviewed compensation package.
•Country vacation package that increases with your tenure.
•Country-specific benefits offering incl. private health care, fitness and meal allowances.
•Annual personal development budget to increase your impact.
•Hybrid working mode, plus up to 3 months of the year work from anywhere.
•All the best kit and tools to work effectively.
•Annual in-person all-company event and celebration in Europe.
•Working with an exceptional team, doing some of the best work of your career.
