Software Engineer – Profile Matching, Data & AI Platforms (m/f/d)

O projekcie:
ALM Services Technology Group develops end–to–end Web and Mobile Solutions. We work closely with customers usually in long term relations.
Our mission is to create the best possible environment of work for our people, engage in innovative projects, and help to strengthen and develop new competences.

ALM was founded in 2009 in Poland. In 2022 we opened a branch in Budapest, and we are actively working on growing our team in Hungary.

ALM Services Technology Group comprises creative, open-minded individuals who develop innovative solutions daily to help our clients expand their businesses.

Our mission is to create the best possible environment of work for our people, engage in innovative projects, and help to strengthen our competences.

Since 2020 we have been cooperating with our partner, a multinational company working in a med-tech and analytics space. A recognized global leader still willing to challenge the status quo to improve patient care.

We have helped and supported them through various stages of growth. We have built multiple applications for them. We have the core team and know-how in place to help them grow further.

Wymagania:
We are looking for a Mid-Level Software Engineer to help build a production platform for collecting, processing, matching, and enriching profile, entity, and content data from multiple sources.This is a hands-on implementation role. You will build data-integration pipelines and AI-powered components in service of profile/entity matching, and contribute to backend services across the platform — including some full-stack work.
This Role Is a Strong Fit If You Have- 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.Required Experience- 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.Technology ExpectationsPractical experience with several of the following:- 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.Experience with RAG, AI agents, or LLM orchestration frameworks is welcome, but is not a requirement at this level.

Codzienne zadania:
- 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.