AI/ML Engineer
Posted Updated
Description
- Design and build agentic systems that plan, call tools and automate real business workflows
- Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration
- Work with vector databases and search: indexing strategies, hybrid and semantic search, relevance tuning
- Integrate AI services with external systems through APIs: REST endpoints, authentication, webhooks, third-party and client-side SaaS platforms
- Perform prompt engineering, model selection and systematic evaluation of LLM outputs
- Build scalable Python services and the data flows behind them including AI-driven data access such as Text2SQL
- Use AWS cloud to implement AI solutions such as Bedrock, SageMaker, Lambda, Textract
- Bachelor's degree in Computer Science, Information Technology, or a related field
- 3+ years of professional engineering experience including recent hands-on work on AI projects
- Strong proficiency in Python and hands-on experience with the GenAI ecosystem such as LangChain, LlamaIndex, agent frameworks, LLM provider SDKs, Pydantic
- Solid understanding of LLM application concepts including RAG, embeddings, vector databases, tool calling, agent patterns, prompt engineering and evaluation
- Proven experience designing, consuming and integrating APIs and connecting AI services to existing systems
- Working knowledge of AWS including hands-on use of at least one of its AI/ML or serverless services
- Good command of SQL and a working understanding of core data engineering concepts such as ETL, pipelines, data modelling
- Excellent problem-solving and communication skills and the ability to work independently and collaboratively in a fast-paced environment
- Real project experience with Amazon Bedrock AgentCore and the Strands Agents SDK
- Classical machine learning and pre-LLM NLP experience and the related toolkit such as scikit-learn, pyspark, matplotlib
- Computer vision, recommendation systems, anomaly detection experience
- Experience with ETL processes and tools such as Airflow, AWS Glue
- A company culture based on autonomy and accountability
- Flexible working hours
- Cool office with great location in Budapest, nearby Deak Ferenc Square / Astoria
- Macbook for efficient daily tasks
- Company-sponsored technical trainings
- Company-sponsored trips to relevant professional conferences
- Medicare
- AYCM SportPass contribution, yoga at the office, SnapSoft football
- Cocktail party, team buildings, SnapSoft library
Skills
- Agentic AI
- AI
- Airflow
- Anomaly Detection
- API
- Authentication
- AWS
- AWS Bedrock
- Aws Glue
- Cloud
- Computer Vision
- Data Engineering
- Data Modeling
- Embeddings
- ETL
- Generative AI
- Lambda
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- Matplotlib
- NLP
- Prompt Engineering
- Pydantic
- PySpark
- Python
- RAG
- Recommendation Systems
- SaaS
- SageMaker
- scikit-learn
- Semantic Search
- Serverless
- SQL
- Vector Databases
- Webhooks