AI Engineer

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

AI Engineer

POSITION PURPOSE:

AI Engineers are full members of an agile development team. They interact with product management, customers, and engineers on their and related teams while applying their own experiences to build relevant technical solutions to business problems. They seek out and own mid- to long-term deliverables while refining their domain and technical knowledge. They also mentor and coach more junior engineers while building relationships with senior engineers across the company.

ROLE AND RESPONSIBILITIES:

• Lead and participate in design sessions with Enterprise and Hub Data Stewards, Engineering teams, Data Scientists, Product Managers, business and IT stakeholders, that result in design documentation for data processing, storage and delivery solutions.
• Understand business capability needs and processes as they relate to IT solutions through partnering with Product Managers and business and functional IT stakeholders, and apply this knowledge to identifying business problems that could be solved.
• Evaluate new technologies, like Domino or Redshift, or new languages, like Go or React, including performing POCs and presenting results to others, with a goal of providing technical recommendations.
• Challenge the team to improve processes and methodologies, like SCRUM or Kanban, and/or initiate piloting new ones.
• Implement data solutions according to design documentation using a variety of tools and programming languages, like Kafka, SQL and non-SQL databases, Scala, Go etc., following team’s established processes and methodologies, like SCRUM or Kanban.
• Facilitate and participate in code reviews, retrospectives, functional and integration testing and other team activities focused on improving quality of delivery.
• Provide reliable estimates for short term projects and assist in large scale project estimation.
• Collaborate with other data engineers and stewards within the team and across data, technical platforms and product teams on aligning roadmaps, delivery dates and integration efforts.
• Mentor junior and aspiring Data Engineers on the team and across the data community.
• Represent the team at various cross team meetings and events focused on design and planning, like Scrum of Scrums and Release Planning, sharing the results of team efforts, or brainstorming on process improvements.
• Create and maintain design and code documentation in GitHub, Haystack.

KEY WORKING RELATION:

• Works daily with a team of Data Engineers, Data Stewards, and Data Scientists, where applicable.
• Collaborates with Product Management to manage project priorities, deadlines and deliverables.
• Interact regularly with Business Users throughout the project lifecycle.
• Engages with relevant technical teams to get support throughout the
• development process, as needed.
• Interacts with engineers across the team and related teams.
• May lead department teams and be active in inter-department teams
• Has begun to build organization wide relationships.
• Gets along well in an expanded team.
• Actively solicits feedback from project members and looks for the right solution to problems.
• Able to mentor other more junior staff and leverage their time for the larger
• whole (delegation) and is comfortable with a change in direction.
• Knows the difference between a technical and non-technical issue and knows
• when additional stakeholders need to be involved.
• Able to clearly communicate the progress of a small team. Is a strong communicator and can represent technical material at an appropriate level for the audience.

WHO YOU ARE:

• Bachelor’s degree in Computer Science, Software Engineering, or related
• field. Additional 3 years of relevant experience is an acceptable substitute for the degree requirement
• 8-10 years professional Data engineering experience.
• An advanced degree in a relevant field counts as 2 years (Masters) or 4 years (PhD) of experience 2-4 years of AI/ML experience 5+ years

Professional software engineering experience to include:

• Strong understanding of embeddings, cosine similarity, vector search and Retrieval-Augmented Generation (RAG).
• Proven experience in fine-tuning large language models (LLMs).
• Proficiency in Python and familiarity with Pydantic models, Jinja, API, Dockers.
• Hands-on experience with LangChain and/or LangGraph frameworks.
• Programming Languages: Proficiency in Python, R, and SQL for agricultural data analysis and model development.
• AI/ML Frameworks: Experience with TensorFlow, PyTorch, scikit-learn and agricultural-specific ML libraries
• Computer Vision: Expertise in image processing for crop monitoring, disease detection, and automated harvesting using OpenCV and specialized agricultural vision libraries
• IoT & Sensor Data: Experience working with agricultural IoT sensors, weather stations, and precision farming equipment data
• Geospatial Analysis: Knowledge of GIS systems, satellite imagery processing, and spatial data analysis tools like GDAL and PostGIS
• Cloud Platforms: Experience with AWS, Azure, or Google Cloud, particularly their agricultural and IoT services
• Time Series Analysis: Expertise in analyzing temporal agricultural data including weather patterns, crop growth cycles, and seasonal trends
• Familiarity with the relevant industry trends

Desired experience with:

• Familiarity with MCP and A2A frameworks
• Understanding of self-attention mechanisms and Attention-RAG
• Specialized AI Skills
• SLM Fine-tuning: Experience with fine-tuning language models on agricultural datasets and implementing PEFT techniques
• LangGraph & Agentic AI: Proficiency in designing multi-agent systems for agricultural applications
• Context Engineering: Expertise in prompt engineering and RAG systems
• for agricultural knowledge management
• Edge AI: Experience deploying AI models on resource-constrained agricultural devices

Ever feel burnt out by bureaucracy? Us too. That’s why we’re changing the way we work— for higher productivity, faster innovation, and better results. We call it Dynamic Shared Ownership (DSO). Learn more about what DSO will mean for you in your new role here https://www.bayer.com/en/strategy/strategy

Bayer does not charge any fees whatsoever for recruitment process. Please do not entertain such demand for payment by any individuals / entities in connection with recruitment with any Bayer Group entity(ies) worldwide under any pretext.

Please don’t rely upon any unsolicited email from email addresses not ending with domain name “bayer.com” or job advertisements referring you to an email address that does not end with “bayer.com”.