pragmatike - Senior Product Engineer (Remote EMEA)
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Requirements
• Industry: Enterprise Software / AI / Data Infrastructure • 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 modeling, and cloud-based architectures • Hands-on experience with modern cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes) • Experience working with databases and data systems (e.g., PostgreSQL; 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 early-stage startups or building systems from scratch
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 • 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 (PostgreSQL, 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 containerized 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
Benefits
• 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 • Pragmatike is committed to a fair, transparent, and inclusive recruitment process. We do not discriminate based on age, disability, gender, gender identity or expression, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. • In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely, and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration.
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