Senior AI Engineer

Bayer is hiring for a Senior AI Engineer role focused on AI and LLM operations engineering. The position involves working at the intersection of software engineering, data engineering, and applied AI to design and operate multi-agent AI systems and integrate LLM-powered capabilities into enterprise platforms.

• Strong programming skills in Python and experience building production-grade systems
• Experience with CI/CD pipelines, GitHub workflows, version control, and modern SDLC practices
• Deep understanding of production system operations including monitoring, logging, debugging, and incident response
• Solid foundation in data engineering, data pipelines, SQL, and experience with relational and NoSQL databases
• Understanding of data quality, governance, and metadata management
• Experience with at least one major cloud platform (AWS, Azure, or GCP) and infrastructure-as-code
• Knowledge of security, governance, and compliance in data and AI systems
• Production engineering mindset with experience in deploying and maintaining reliable systems
• Strong data and systems thinking for designing maintainable data flows and architectures
• Excellent written and verbal communication skills for documentation and cross-team collaboration
• High learning agility and adaptability with self-directed learning in AI/ML
• Active interest and hands-on experimentation with LLMs and AI tools including prompt engineering

Nice to have:

• 5+ years software engineering experience including 3+ years in data engineering or analytics infrastructure
• Experience with data warehousing platforms like Snowflake, BigQuery, Redshift
• Experience with workflow orchestration tools such as Airflow, Prefect, Dagster
• Background in search, recommendation systems, or information retrieval
• Exposure to AI/ML side projects, hackathons, or proof-of-concepts
• Experience with vector databases and semantic search technologies
• Prior work on LLM-powered applications and knowledge of AI safety and ethical AI
• Knowledge of multi-agent frameworks like LangGraph, AutoGen, CrewAI
• Experience with developer experience, platform engineering, or internal tooling
• Background in analytics and measurement frameworks, open-source contributions
• Experience in regulated industries such as pharmaceuticals, finance, or healthcare

• Design and implement multi-agent orchestration systems coordinating AI agents across complex workflows
• Build autonomous SDLC pipelines with AI agent support and human oversight
• Integrate AI systems with engineering infrastructure including GitHub, CI/CD pipelines, and testing frameworks
• Develop natural-language query interfaces over enterprise data combining structured and unstructured sources
• Build explainability, guardrails, and scope-management layers to improve AI workflow accuracy and trust
• Design and operate data and system architectures for reliable AI operations including monitoring and incident response
• Collaborate with cross-functional teams to translate business and data requirements into AI technical solutions