Principal Backend Engineer (Remote EMEA)
Indexed description
Start date: ASAP
Languages: Fluent English required
Industry: Enterprise Software / AI / Data Infrastructure
About The Role
Pragmatike is recruiting on behalf of a fast-growing, AI-first enterprise software company building a next-generation semantic intelligence layer for large-scale business data.
Their platform sits on top of complex enterprise systems and transforms fragmented, highly customized data into structured, business-meaningful information that AI systems can reliably understand and act on. By bridging the gap between raw enterprise data and AI, they enable more accurate automation, decision-making, and scalable intelligence across organizations.
We are seeking a Senior Backend Engineer with strong experience in building data-intensive, production-grade systems. This is a highly technical, hands-on role focused on designing and owning core backend infrastructure that powers semantic data processing and intelligent applications.
You will play a key role in shaping the platform from the ground up, working across data pipelines, backend services, and APIs. This position requires a strong product mindset, architectural ownership, and the ability to operate effectively in a fast-moving, early-stage environment.
Your Responsibilities
- Design, build, and own backend systems that transform raw enterprise data into structured, business-meaningful representations
- Develop and maintain scalable data processing pipelines, semantic storage layers, and versioning systems
- Own features end-to-end, from data modeling and backend logic to API design and integration layers
- Make and defend architectural decisions, balancing long-term scalability with short-term execution speed
- Build robust, production-grade APIs and services to power internal and external applications
- Integrate modern AI tools into development workflows to accelerate implementation, testing, and documentation
- Collaborate closely with cross-functional teams to deliver high-quality, impactful features
- Contribute to engineering best practices and help shape a scalable, maintainable platform architecture
- 5+ years of experience as a Backend Engineer, Software Engineer, or Product Engineer in a SaaS or product-driven environment
- Strong experience building data-intensive or distributed systems in production
- Proficiency in backend development (e.g., Python, Java, or similar languages)
- Solid understanding of APIs, data modeling, and cloud-based architectures
- Experience working with modern cloud platforms (AWS, GCP, or Azure) and containerized environments
- Ability to make pragmatic technology choices based on problem context rather than fixed stack preferences
- Strong problem-solving skills and ability to break down complex systems into scalable solutions
- Clear communication skills, with the ability to explain technical decisions to both technical and non-technical stakeholders
- Collaborative mindset with a strong sense of ownership and accountability
- Experience using AI-assisted development tools in a practical, productivity-focused way
- Experience with data pipelines, ETL/ELT systems, or large-scale data processing architectures
- Familiarity with semantic systems such as knowledge graphs, ontology mapping, or data catalogs
- Exposure to enterprise systems or complex ERP environments
- Experience with graph databases (e.g., Neo4j) or analytics platforms
- Background in AI/ML systems or integrating AI models into production workflows
- Previous experience in early-stage startups or building systems from scratch
- Build foundational technology enabling AI to operate reliably on complex enterprise data
- Take ownership of core backend systems in a high-impact, early-stage environment
- Work on technically challenging problems at the intersection of data, AI, and enterprise software
- Join a highly collaborative, product-focused team with strong engineering standards
- Gain exposure to cutting-edge approaches in semantic data modeling and AI integration
- Grow with a company that values transparency, ownership, and long-term impact
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