Applied AI Engineer: Build Agentic AI for Manufacturing

BoWatt GmbH; Germany (OH); On-site; USD 81,000 - 115,000; Full time

Benefits offered by this job

Fully remote, hybrid, or onsite

Top-tier hardware

Job summary

BoWatt GmbH is seeking a software engineer to build AI-powered features using large language models. You will collaborate with stakeholders to identify high-impact use cases that improve customer experience and design multi-step agent workflows that reason over requirements and system specs.

You will integrate AI capabilities with internal data sources and work with the engineering team to deploy features into production environments, owning implementations end to end in a startup setting.

Qualifications

• 3+ years of software engineering experience, with at least 1 year working with LLMs.
• Experience integrating AI capabilities using various APIs and tools.
• Comfortable owning implementations end to end in a startup setting.
• Knowledge of security, data privacy and data hygiene around integration.
• Wosters with initiative and ability to learn required tools on the job.

Responsibilities

• Design and implement AI-powered features using existing large language models.
• Collaborate with stakeholders to identify AI use cases for customer experience.
• Build multi-step agent workflows that reason over documents and specs.
• Integrate AI systems with internal data sources to expand agent knowledge.
• Work with engineering to deploy AI features into production environments.

Skills

LLMs

AI integration

End-to-end ownership

Security and data privacy

Startup mindset

Tools

LangChain

LlamaIndex

Qdrant

Weaviate

pgvector

Azure AI Foundry

React

Job description

BoWatt GmbH is seeking a software engineer to build AI-powered features using large language models. You will collaborate with stakeholders to identify high-impact use cases that improve customer experience and design multi-step agent workflows that reason over requirements and system specs.

You will integrate AI capabilities with internal data sources and work with the engineering team to deploy features into production environments, owning implementations end to end in a startup setting.