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AI Engineer - Job Opportunity at Circonomit

Cologne, Germany
Full-time
Mid-level
Posted: July 7, 2025
On-site
EUR 50,000 - 100,000 per year

Benefits

Competitive salary packages that position compensation within market standards for AI engineering roles
Equity packages providing ownership stake in early-stage company with potential for significant returns
Decision-making authority and ownership responsibilities that accelerate professional development
Sports and fitness benefits supporting work-life balance and team building
Early-stage company environment offering rapid skill development and diverse project exposure

Key Responsibilities

Architect and design ontological frameworks and knowledge schemas that form the foundation of organizational digital twins, directly impacting strategic decision-making capabilities
Lead integration of advanced LLM technologies including LangChain and RAG systems to automate complex data transformation processes at enterprise scale
Drive knowledge graph operations encompassing data ingestion, enrichment, and alignment that enable comprehensive organizational resource understanding
Transform unstructured business data into actionable structured graphs using cutting-edge AI tools and prompt engineering methodologies
Deliver rapid prototyping of AI functionalities that create measurable customer impact and competitive advantage
Conduct experimental validation and optimization of AI models to ensure performance standards that meet enterprise requirements
Maintain and monitor AI system performance with proactive issue identification and resolution capabilities
Provide technical leadership and AI expertise to cross-functional teams while staying current with emerging AI technologies and methodologies

Requirements

Education

Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field

Experience

Advanced experience with AI frameworks and proven experience in developing and deploying algorithms for knowledge extraction and modeling

Required Skills

Proficiency in LLMs, prompt engineering, embeddings, and RAG workflows Strong programming skills in Python or similar languages used in AI development Advanced experience with frameworks such as LangChain and spaCy Proven experience in developing and deploying algorithms towards knowledge extraction, mapping, and modeling for large amounts of information Relevant experience and understanding of transparency and explainability of models, applying ontology logics and data lineage Experience with Foundry, Grakn English and German at level C1 or higher
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Sauge AI Market Intelligence

Industry Trends

The enterprise AI market is experiencing unprecedented growth with organizations increasingly adopting AI-driven decision-making systems, particularly in resource optimization and operational efficiency domains. Knowledge graphs and semantic AI technologies are becoming critical infrastructure components for large organizations seeking to understand complex interdependencies within their operations. Large Language Models integration with enterprise systems represents a rapidly expanding market segment, with companies investing heavily in RAG architectures and prompt engineering capabilities to transform unstructured data into actionable insights. The demand for professionals who can bridge traditional AI/ML expertise with modern LLM technologies is creating significant opportunities. The concept of 'digital twins' for organizational processes is gaining substantial traction in enterprise software, with companies recognizing the strategic value of comprehensive system modeling for predictive analytics and risk management. This trend is driving demand for AI engineers who can work with ontological frameworks and knowledge representation systems.

Salary Evaluation

The EUR 50,000-100,000 range is competitive for mid-level AI engineers in the German market, particularly in Cologne where tech salaries are generally lower than Munich or Berlin. The wide range likely reflects the early-stage nature of the company and their willingness to adjust compensation based on candidate experience level. The equity component adds significant potential value given the company's positioning in the growing enterprise AI market.

Role Significance

Given the early-stage nature and comprehensive responsibilities, this role likely involves working within a small, agile team of 5-10 engineers where individual contributions have outsized impact on product development and company direction.
This role represents a senior individual contributor position with significant technical ownership and strategic impact. The responsibilities indicate substantial autonomy in architectural decisions and direct influence on product development, suggesting a role that bridges senior engineer and technical lead responsibilities.

Key Projects

Development of enterprise-scale knowledge graph platforms that integrate multiple data sources and provide real-time insights for organizational decision-making Implementation of advanced RAG systems for automated document processing and semantic search capabilities across large enterprise datasets Creation of ontological frameworks for business process modeling that enable predictive analytics and risk assessment for complex organizational systems

Success Factors

Deep technical expertise in both traditional AI/ML methodologies and modern LLM technologies, with the ability to architect solutions that effectively combine these approaches for enterprise-scale applications Strong product intuition and customer focus to translate complex technical capabilities into compelling user experiences that deliver measurable business value Rapid prototyping and experimentation skills that enable quick validation of AI concepts and iterative improvement based on user feedback and performance metrics Excellent communication abilities to work effectively with cross-functional teams and provide technical leadership on AI initiatives while explaining complex concepts to non-technical stakeholders

Market Demand

High demand exists for AI engineers with LLM and knowledge graph expertise, as this combination of skills is relatively rare in the current market. The specific focus on enterprise applications and semantic modeling creates additional scarcity, positioning qualified candidates favorably for negotiation and career advancement.

Important Skills

Critical Skills

LLM and RAG expertise is absolutely essential as these technologies form the core of the company's data processing and knowledge extraction capabilities. The ability to effectively prompt engineer and integrate these systems directly impacts product functionality and customer value delivery. Knowledge graph and ontological modeling skills are fundamental to the company's core value proposition of creating comprehensive organizational understanding. These capabilities enable the semantic relationships and structured data representation that differentiate the product from traditional analytics solutions. Python programming proficiency with AI/ML frameworks is critical for implementation and deployment of the complex AI systems described in the role. The ability to rapidly prototype and iterate on AI solutions directly impacts the company's ability to respond to customer needs and market opportunities.

Beneficial Skills

Enterprise software development experience would be valuable given the B2B nature of the company's solutions and the need to integrate with existing organizational systems and workflows Business process modeling and analysis skills would enhance the ability to translate customer requirements into effective AI solutions and improve the relevance of the semantic models being developed Cloud platform expertise (AWS, Azure, GCP) would support the scalability and deployment requirements of enterprise AI solutions, particularly as the company grows and serves larger customers

Unique Aspects

The role combines cutting-edge LLM technologies with traditional enterprise AI applications, offering exposure to both emerging and established AI methodologies within a single position
Focus on organizational 'digital twins' and interdependency modeling represents a sophisticated approach to enterprise AI that goes beyond typical business intelligence or automation applications
Early-stage company environment with equity participation provides opportunity for significant professional and financial growth as the company scales
The specific requirement for both English and German fluency opens opportunities for international business development and European market expansion

Career Growth

Career progression to senior technical roles typically occurs within 2-4 years given the comprehensive experience and technical leadership opportunities. Transition to management or executive roles may take 4-6 years depending on company growth and individual leadership development.

Potential Next Roles

Senior AI Engineer or Principal AI Engineer roles at larger technology companies focusing on enterprise AI solutions AI/ML Team Lead or Technical Lead positions overseeing AI product development and engineering team management AI Solutions Architect roles at consulting firms or enterprise software companies specializing in digital transformation initiatives Chief Technology Officer or VP of Engineering positions at early-stage companies, particularly given the entrepreneurial experience gained in this role

Company Overview

Circonomit

Circonomit appears to be an early-stage startup focused on enterprise resource optimization and organizational intelligence, positioning itself in the growing market for AI-driven business intelligence and digital transformation solutions. The company's focus on 'strategic twins' and comprehensive resource understanding suggests a sophisticated approach to enterprise AI applications.

As an early-stage company, Circonomit is likely competing with established enterprise software providers and other AI startups in the business intelligence and resource optimization space. Their specific focus on interdependency modeling and resource impact analysis may provide differentiation in a crowded market.
Based in Cologne, Germany, the company operates within the European enterprise software market, which provides access to both local German enterprises and broader European Union markets. The German location offers advantages in terms of data privacy compliance and access to skilled technical talent.
The company culture emphasizes rapid development, high performance standards, and individual ownership, as evidenced by their 'hustle the day, analyze at night' philosophy. This suggests an intense but rewarding work environment suitable for ambitious professionals seeking significant impact and growth opportunities.
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  • Salary estimates and market demand analysis
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  • Critical success factors and key skills
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