As a key member of theAI & Knowledge Search project, you will be part of a passionate team that supports Boehringer Ingelheim employees across all departments to find insights from documents and help AI application builders develop solutions that save time and support innovation.TheLead Backend Engineer / Tech LeadinAI & Knowledge Searchis a role that combines hands‑on backend engineering with system ownership, vendor management, and architectural responsibilities. You will create innovative solutions that combine traditional software engineering (Python/AWS) with modern Generative AI approaches (RAG/Agents). You will provide technical leadership and hands‑on guidance to a team of distributed engineers.
In this role, you will extend our scalable platform for AI application builders with new tools. You will bring new ways of accessing knowledge to our employees built on top of this platform, for example with our new conversational search agent. You will work in an instruction‑free agile environment, taking full ownership of the applications we build, lead the technical direction and its implementation.
Tasks and responsibilities
* System Ownership & Governance:Act as the primary System Lead, maintaining lifecycle documentation, managing environments (Dev/QA/Prod), and ensuring adherence to ITIL, and BI architecture and development standards. You will be responsible for the setup of AI evaluation and monitoring frameworks (e.g., Langfuse) to continuously measure model performance and reliability.
* AI Solution Design & RAG Architecture:Design and implement advanced Retrieval‑Augmented Generation (RAG) and agentic systems to improve the accuracy and speed of the knowledge search application.
* Backend Development & Code Quality:Develop high‑quality, modular, and maintainable Python services. You will support complex data workflows with a strict focus on code quality (Type Hinting, PyTest, Pydantic).
* Data Pipeline Engineering & Integration:Implement robust document processing pipelines using tools likeDocling, AWS Glue, andApache Airflowto prepare unstructured data for AI consumption. You will also execute complex system integrations across the enterprise landscape using platforms likeSnaplogic.
* Cloud & Container Management:Manage and optimize AWS cloud infrastructure (ECS, EC2) to ensure applications are scalable, secure, and cost‑efficient. You will manage containerized workloads (Docker) and own the CI/CD deployment processes.
* Operational Excellence & Vendor Management:Lead the technical guidance for the external vendor teams primarily developing the solution. You will be responsible for internalizing knowledge from these partners, validating their deliverables in sprint reviews, and ensuring technical alignment with our architectural standards.
Requirements
* Education:Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
* Experience:8+ years in backend engineering with significant exposure to full‑stack development, system integration, and system ownership. 2+ years leading a team of engineers, an advantage is experience with external vendor teams.
* Advanced Software Engineering:Deep expertise in software engineering fundamentals, focusing on modularity, testability, and architectural patterns for complex application and data workflows.
* Generative AI & LLM Architecture:Experience designing RAG architectures and Agentic Workflows. Familiarity with LangChain, LlamaIndex, and Vector Databases (Pinecone, Milvus, or Chroma).
* Cloud & DevOps:Proficiency in managing scalable AWS cloud infrastructure (ECS, EC2, VPC, Lambda among others) and implementing Infrastructure as Code (Terraform, CloudFormation, or AWS CDK).
* Soft Skills:High level of autonomy (ability to translate sprint goals into clear technical requirements without detailed instruction), strong communication skills for stakeholder management, and discipline in documenting architectural decisions.
* Desirable Data Engineering:Experience transforming unstructured data into structured formats (using Apache Airflow, AWS Glue, or OCR) is highly desirable.
* Integration Expertise:Familiarity withSnaplogicis preferred.
* Semantic Technologies:Exposure to Semantic Data/Knowledge Graphs (Neo4j, RDF/SPARQL) is considered a strong plus.
* AI Evaluation:Experience with LLM evaluation tools (Langfuse, Arize, MLflow) is an advantage.
We are continuously working to design the best experience for you. Here are some examples of how we will take care of you:
* Flexible working conditions
* Life and accident insurance
* Health insurance at a competitive price
* Investment in your learning and development
If you have read this far, what are you waiting for to apply? We want to know more about you!
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