Senior Product Engineer; Remote EMEA

Location: Fully remote (EMEA timezone)

Start date: ASAP

Languages: Fluent English required

Industry: Enterprise Software / AI / Data Infrastructure

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.

• 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
• Build and operate high‑performance APIs and real‑time services (REST, Server‑Sent Events)
• Architect and optimize distributed systems and data‑intensive workflows using modern cloud infrastructure
• Work with relational and graph databases (Postgre
  
  SQL, Neo4j) and data platforms like Snowflake
• Make and defend architectural decisions, balancing long‑term scalability with short‑term execution speed
• Deploy and manage services in containerised environments (Docker, Kubernetes) across Azure and Google Cloud
• Integrate modern AI tools into development workflows to accelerate coding, 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), with strong preference for Python (async frameworks like FastAPI)
• Solid understanding of APIs (REST), real‑time communication patterns (e.g., SSE), data modelling, and cloud‑based architectures
• Hands‑on experience with modern cloud platforms (AWS, GCP, or Azure) and containerised environments (Docker, Kubernetes)
• Experience working with databases and data systems (e.g., Postgre
  
  SQL; familiarity with graph databases is a plus)
• 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
• Experience with graph databases (e.g., Neo4j) or analytics platforms
• Exposure to enterprise systems or complex ERP environments
• Background in AI/ML systems or integrating AI models into production workflows
• Experience with streaming systems (e.g., Kafka) and modern data platforms (e.g., Snowflake)
• Previous experience in…