Lead Backend Engineer – AI Platform
As a key member of the AI & 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.
The Lead Backend Engineer / Tech Lead in AI & Knowledge Search is 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 like Docling, AWS Glue, and Apache Airflow to prepare unstructured data for AI consumption.
You will also execute complex system integrations across the enterprise landscape using platforms like Snaplogic
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)
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 - 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)
Desirable - Data Engineering:
Experience transforming unstructured data into structured formats (using Apache Airflow, AWS Glue, or OCR) is highly desirable
Desirable - Integration Expertise: Familiarity with Snaplogic is preferred
Desirable - Semantic Technologies: Exposure to Semantic Data/Knowledge Graphs (Neo4j, RDF/SPARQL) is considered a strong plus
Desirable - AI Evaluation: Experience with LLM evaluation tools (Langfuse, Arize, MLflow) is an advantage
#IamBoehringerIngelheim because…
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
Gym membership discounts
If you have read this far, what are you waiting for to apply? We want to know more about you
Nuestra compañía
En Boehringer Ingelheim desarrollamos tratamientos innovadores que mejoran la vida de las personas y de los animales. Fundada en 1885 y de propiedad familiar desde entonces, Boehringer Ingelheim adopta una perspectiva a largo plazo. En la actualidad, contamos con empleados en todo el mundo que fomentan una cultura diversa, colaborativa e integradora.
Creemos que si contamos con personas talentosas y ambiciosas, apasionadas por la innovación, no hay límite a lo que podemos lograr.
¿Por qué Boehringer Ingelheim?
Con nosotros puedes crecer, colaborar, innovar y mejorar vidas.
Ofrecemos un trabajo estimulante en un entorno laboral general respetuoso y cordial, rodeado de un mundo de mentalidades y prácticas impulsadas por la innovación.
Además, el aprendizaje y el desarrollo de todos los empleados es clave, porque tu crecimiento es nuestro crecimiento.
Boehringer Ingelheim es una empresa global que ofrece igualdad de oportunidades y se enorgullece de mantener una cultura diversa e inclusiva.
Aceptamos la diversidad de perspectivas y nos esforzamos por crear un entorno integrador, que beneficie a nuestros empleados, pacientes y comunidades.
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