Our Customer:
A global pharmaceutical company and one of the world’s leading manufacturers of generic and specialty medicines. You will join the AI team that builds AI-native products for R&D, Manufacturing, Supply Chain, Commercial, Finance and Procurement.
Your Tasks:
- Translate ambiguous business requirements from stakeholders across R&D, Manufacturing, Supply Chain, Commercial, Finance and
- Procurement into AI-native solutions with measurable ROI
- Prototype rapidly with real or synthetic enterprise data and take solutions from POC through MVP to scalable production services
- Design and implement RAG pipelines, copilots and agentic workflows on Azure AI Foundry, Azure OpenAI and Databricks
- Define guardrails and governance, including model validation, evaluation frameworks, safety and compliance checks
- Deploy and maintain AI components on Azure, monitoring their performance, cost and quality
- Produce architecture diagrams, design docs and other technical documentation
- Collaborate with full-stack and frontend engineers, QA and product on integration, AI output quality and the roadmap
Required Experience and Skills:
- 5+ years of experience in software or data engineering
- 2+ years of experience building LLM applications in production, with measurable business impact
- Strong command of Python and writing clean, production-grade code
- Hands-on experience with LLM application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel or equivalent agent frameworks
- Hands-on experience building agentic AI systems in production, including tool use, autonomous workflows and multi-agent orchestration with planner/executor or supervisor patterns
- Deep understanding of RAG patterns, including chunking, embeddings and retrieval evaluation
- Hands-on experience with vector databases such as Azure AI Search, pgvector, Pinecone or Weaviate
- Solid understanding of prompt engineering and structured output design
- Hands-on experience with LLM evaluation and observability using LangSmith, Langfuse or in-house eval harnesses, including offline and online quality measurement
- Hands-on experience with Azure AI Foundry and Azure OpenAI
- Hands-on experience with Databricks
- Hands-on experience building APIs and microservices on Azure
- Hands-on experience with CI/CD for AI workloads and Git
- Working knowledge of API, web service and data security practices
- Working knowledge of React or Streamlit sufficient to integrate AI features into user interfaces
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science or a related field
- Proven ability to explain AI capabilities to business stakeholders in terms of business value
- Proven ability to work independently with minimal supervision and as a reliable team player
- English – B2
Would Be a Plus:
- Experience in regulated industries such as pharma, healthcare or finance, including familiarity with compliance constraints
- Hands-on experience with fine-tuning, distillation or other model adaptation techniques
- Open-source contributions to the LLM or AI agents ecosystem
Working conditions
5-day working week, 8-hour working day;
Remote work.