Software Engineer – Profile Matching Data & AI Platforms m/f/d, REMOTE WROCŁAW KATOWICE

• solid Python software engineering experience;
• experience building or maintaining production systems that process multi-source content or profile/entity data;
• hands-on experience integrating internal and third-party REST APIs (authentication, pagination, retries, backoff, caching, rate limits);
• experience building data-integration / ETL pipelines that support matching and enrichment use cases;
• exposure to profile/entity matching concepts — deduplication, fuzzy matching, or basic use of embeddings;
• practical experience with LLM APIs, prompting, structured outputs, classification, summarisation, or extraction;
• understanding of embeddings, vector similarity, semantic search, deduplication, or clustering;
• comfort working across the stack — some full-stack / UI experience (Node.js / React) is a plus;
• ability to write clean, testable code and communicate technical decisions clearly;
• experience using AI-assisted development tools while remaining responsible for quality, security, and correctness.

• 3+ years of experience in Software Engineering, Backend Engineering, Data Engineering, or Platform Engineering;
• strong commercial experience with Python;
• experience integrating and operating third-party REST APIs;
• experience with ETL processes, ingestion services, and batch or event-driven pipelines;
• knowledge of SQL and relational databases, preferably PostgreSQL;
• experience with Snowflake, Parquet, object storage, or an equivalent analytical environment;
• experience with Airflow, cron, or similar orchestration tools;
• familiarity with LLM APIs, prompting, embeddings, or semantic retrieval;
• experience with automated testing, CI/CD, version control, and code review;
• some full-stack exposure (Node.js / React) is a strong plus;
• good communication skills and fluent English.

• Python and modern backend or data-processing frameworks;
• REST APIs, OAuth, pagination, retries, caching, and fault-tolerant integrations;
• data-integration / ETL pipelines built in service of profile/entity matching;
• Airflow, cron, or equivalent orchestration tooling;
• PostgreSQL, Snowflake, Parquet, or object storage;
• LLM APIs, prompting, structured outputs, classification, or extraction;
• embeddings, vector databases, semantic search, deduplication, and clustering (basics);
• microservices and platform / systems integration;
• Docker and cloud infrastructure (AWS / Azure);
• CI/CD and production deployment;
• Node.js / React — full-stack capability is valued over pure data-engineering specialisation;
• AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or equivalent.

,[build and maintain services for collecting, normalising, matching, enriching, and delivering profile, entity, and content data;, contribute to profile/entity matching — deduplication, fuzzy matching, and support for rules/embeddings-based approaches;, develop data-integration pipelines as part of matching and enrichment workflows;, implement AI enrichment using LLM APIs, prompting, structured outputs, and embeddings;, build classification, summarisation, ranking, semantic matching, and deduplication mechanisms;, support orchestration (Airflow / cron), incremental processing, backfills, and reprocessing;, contribute to data models and multi-source catalogs using PostgreSQL, Snowflake, or Parquet;, integrate internal and third-party REST APIs (authentication, pagination, retries, caching, failures, API changes);, develop backend services and internal APIs, including some full-stack / UI work in Node.js / React;, monitor pipeline health, data freshness, completeness, and data quality;, support automated testing, CI/CD, code review, releases, and production operations;, write secure, testable, and maintainable Python code;, collaborate with product, data, AI, and engineering teams;, use AI-assisted development tools while remaining responsible for code quality and correctness.] Requirements: Python, REST API, ETL, SQL, Relational database, Snowflake, Storage, Airflow, Automated testing, CD, OAuth, Microservices, Docker, Cloud, AWS, Azure, AI, PostgreSQL, Node.js, React Tools: Agile, Scrum. Additionally: Private healthcare, Flat structure, Small teams, International projects, Salary in foreign currency, Workation, Flexible hours, Certificates.