Senior Automation Engineer

Company DescriptionAgentic GmbH builds advanced agentic AI research systems for life sciences and financial services. Our platforms combine autonomous reasoning, real-time data ingestion, multimodal analysis, and knowledge-driven workflows. We help organizations evolve from static reporting to continuously learning research systems — enabling faster discovery, deeper insight generation, and resilient decision-making across complex domains.Role Description — Senior Automation Engineer (Agentic AI)We are seeking a Senior Automation Engineer with deep expertise in designing and implementing agentic AI workflows. In this role, you will architect, build, and optimize autonomous research pipelines that integrate reasoning models, vector databases, knowledge graphs, and multi-agent frameworks. You will work across both life science and financial-services use cases, ensuring that our systems remain robust, scalable, and capable of continuous learning.Daily responsibilities include designing multi-agent architectures, orchestrating LLM-driven workflows, building high-performance data pipelines, debugging complex agent behavior, and collaborating with cross-functional teams to deliver production-ready systems for clients.QualificationsDeep Python expertise, including experience with async workflows, data pipelines, model orchestration, and production-grade architecture.Hands-on experience with at least two agent frameworks (e.g., LangGraph, Pydantic-AI, LlamaIndex Agents, CrewAI, OpenAI Assistants).Strong familiarity with vector databases such as Pinecone, Weaviate, AstraDB, or Qdrant, including schema design and retrieval optimization.Experience working with or constructing knowledge graphs, ideally with Neo4j or similar graph technologies.Ability to design and maintain autonomous systems that integrate LLMs, tool-calling, retrieval layers, and structured memory.Practical experience in system integration, debugging, and performance tuning within complex AI/ML or data-intensive environments.Solid understanding of CI/CD workflows, containerization, and cloud environments (Azure, AWS, or GCP).Strong analytical and communication skills, with the ability to collaborate across engineering, product, and domain-expert teams.Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Automation, or a related technical field.Nice to HaveExperience in life sciences, biotech R&D, financial markets, or other research-heavy domains.Understanding of multimodal LLM workflows (image, text, structured data).Familiarity with knowledge-curation pipelines and reflective learning systems.