Senior AI Engineer (Forward Deployed)

Senior AI Engineer (Forward Deployed) at KI group Gmb H

About the role

This position centers on the direct, hands-on deployment of AI-powered systems within intricate client environments.

You will serve as the technical bridge between advanced language models, natural language processing capabilities, and the operational realities of customer workflows.

Your work will transform business logic, decision frameworks, and data pipelines into functioning production systems that deliver measurable value.

• Key facts
• Engagement: Permanent, full-time position

What you'll do

• Lead the end-to-end technical implementation of AI solutions directly within customer environments, ensuring that natural language processing, large language models, and speech technology components integrate smoothly with existing infrastructure and business processes.
• Translate complex business requirements, decision‑mandating frameworks, and operational data flows into functional system architectures that meet production standards for reliability, performance, and maintainability.
• Design and build scalable software systems that incorporate advanced AI capabilities while adhering to engineering best practices for code quality, testing, monitoring, and deployment automation.
• Collaborate closely with customer stakeholders to understand their operational challenges, document technical requirements, and iteratively refine solutions based on real‑world feedback and performance metrics.
• Work alongside internal product, research, and engineering teams to ensure that forward‑deployed solutions align with broader platform capabilities and that customer insights inform future product development.
• Architect and implement data processing pipelines that prepare, transform, and manage the information flows required to train, fine‑tune, and operate language models and speech recognition systems in production settings.
• Establish and maintain production‑ready systems that include proper error handling, logging, observability, and incident response procedures to ensure high availability and rapid troubleshooting when issues arise.
• Provide technical guidance and knowledge transfer to customer teams, enabling them to understand, operate, and eventually maintain the AI systems you deploy within their organizations.
• Evaluate and select appropriate technologies, frameworks, and third‑party services that balance technical performance, cost efficiency, and long‑term maintainability for each unique customer environment.
• Document system architectures, integration patterns, and operational procedures in clear, accessible formats that support both technical and non‑technical audiences.

Requirements

• Extensive professional experience in software engineering with a proven track record of building and deploying production systems that handle real user traffic and business‑critical workloads.
• Deep technical expertise in natural language processing, large language models, and speech technologies, including practical experience implementing these capabilities in live environments rather than purely research or experimental contexts.
• Strong programming skills with the ability to write clean, maintainable, and well‑tested code that meets professional engineering standards for production systems.
• Demonstrated ability to work directly with customers or external stakeholders, translating their business needs into technical specifications and managing the iterative process of solution development and refinement.
• Solid understanding of software architecture principles, including how to design systems that scale horizontally, handle failures gracefully, and integrate with diverse technology stacks.
• Experience building data pipelines and managing the full lifecycle of data from ingestion and transformation through to consumption by machine learning models and downstream applications.
• Practical knowledge of deploying and operating AI models in production, including considerations around inference performance, model versioning, monitoring for drift, and managing computational resources efficiently.
• Ability to work independently in customer environments, making sound technical decisions without constant oversight while knowing when to elevate issues or seek input from specialized team members.
• Strong communication skills that enable you to explain complex technical concepts to non‑technical audiences and to document your work in ways that support knowledge transfer and long‑term system maintenance.
• Willingness to travel to customer sites as needed to conduct on‑site implementation work, troubleshooting, and stakeholder engagement.

Skills and tools

• Natural language processing frameworks and libraries for text analysis, entity extraction, classification, and generation tasks
• Large language model platforms including both commercial APIs and open‑source alternatives for fine‑tuning and deployment
• Speech recognition and synthesis technologies for building voice‑enabled applications and processing audio data
• Modern programming languages commonly used in AI engineering and backend development
• Cloud infrastructure platforms for deploying scalable applications and managing computational resources
• Container orchestration and deployment automation tools for managing production services
• Data processing frameworks for building ETL pipelines and managing large‑scale data transformations
• Version control systems and collaborative development workflows
• Monitoring, logging, and observability platforms for production system management
• API design and integration patterns for connecting AI capabilities with existing enterprise systems
• Practical notes

This role requires the ability to work on‑site at customer locations as implementation needs dictate, so flexibility around travel is essential.

The position is based in Cologne and offers permanent employment with KI group Gmb H.

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