Software Engineer AI

Description

In this role you will partner with product and engineering teams at Boehringer Ingelheim, in our BI X business to design, build, and integrate AI-powered solutions into applications that drive meaningful impact in healthcare. You will work across the full AI development lifecycle from rapidly prototyping LLM-based workflows to delivering reliable, well evaluated solutions that teams can build on. If you enjoy experimenting with emerging AI tools, working across disciplines, and turning ideas into working software, you will feel at home at BI X.

In this role you will partner with product and engineering teams at Boehringer Ingelheim, in our BI X business to design, build, and integrate AI-powered solutions into applications that drive meaningful impact in healthcare. You will work across the full AI development lifecycle from rapidly prototyping LLM-based workflows to delivering reliable, well evaluated solutions that teams can build on. If you enjoy experimenting with emerging AI tools, working across disciplines, and turning ideas into working software, you will feel at home at BI X.

Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.

Locatiion is our Ridgefield, CT office. This is a collaborative team and we are 3 days on site. For these roles, we are unable to sponsor the successful candidate for work authorization in the U.S. The successful candidate must be authorized to work in the U.S. without employer sponsorship currently and in the future.

This position offers a base salary typically between $75,000 and 181,000. The position may be eligible for a role specific discretionary bonus, relocation, and/or other compensation elements. We continuously review market data and may adjust salary ranges as needed in the future. Actual compensation will be based on job-related factors such as skills, experience, and qualifications, and other factors permitted by law.

For an overview of our benefits please .

• AI Integration & Development:
  Design and implement LLM-based features and pipelines using frameworks such as Lang Chain and Lang Graph. Build and maintain Retrieval-Augmented Generation (RAG) systems, including vector store management, chunking strategies, embedding pipelines, and retrieval optimization
• Prototyping & Experimentation:
  Rapidly explore and evaluate new AI capabilities, tools, and approaches. Translate ambiguous problem statements into working prototypes that demonstrate value and inform product direction
• Collaboration & Requirements Gathering:
  Meet regularly with IT colleagues, product owners, and stakeholders to understand business needs and translate them into well-scoped AI engineering solutions. Communicate tradeoffs clearly across technical and non-technical audiences
• Application Support:
  Maintain and improve existing AI-integrated systems, troubleshoot pipeline failures, and take corrective action on issues related to retrieval quality, prompt behavior, or model outputs
• Project Participation:
  Contribute to project teams by delivering on assigned tasks and action items, participating in agile ceremonies, and supporting delivery against team goals
• Technical Awareness:
  Stay current with the rapidly evolving AI/ML landscape, including emerging LLM capabilities, new tooling, and best practices for responsible AI development
• Documentation:
  Produce clear documentation for AI workflows, integration patterns, prompt templates, and system architecture in support of both operational and project activities

• Proficiency in Python for AI/ML development and backend service integration
• Hands-on experience with Lang Chain and/or Lang Graph for building agentic and multi-step LLM workflows
• Strong understanding of RAG pipelines end-to-end: document ingestion, chunking, embedding, vector storage, and query-time retrieval
• Familiarity with leading LLM providers and APIs (e.g., OpenAI, Anthropic, Azure OpenAI, AWS Bedrock)
• Experience with evaluation and testing of AI systems, including retrieval quality metrics, LLM output assessment, and regression testing for prompt changes. Understanding of AI observability and experimentation tooling (e.g., Lang Smith, Weights & Biases, or equivalent)
• Working knowledge of vector databases and semantic search principles
• Solid foundation in software engineering practices: version control (Git), CI/CD, and containerization (Docker)
• Effective communication skills with the ability to explain AI system behavior and limitations to non-technical…