Állás részletei
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Cég neve
High Tech Engineering Center Kft.
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Munkavégzés helye
1052, Budapest, Szervita tér 8. -
Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
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Elvárt technológiák
- PYTHON AZURE API DATABASES DEBUGGING CI
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Elvárások
- Angol középfok
- Nem kell tapasztalat
- Középiskola
Kis türelmet...
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Állás leírása
Responsibilities
- Chunking and ingestion architecture with deterministic, validation-gated pipelines handling diverse enterprise document types with indexing and contextual enrichment
- Retrieval pipeline with vector search, BM25 hybrid retrieval, RRF re-ranking, embedding model selection and optimisation
- Agent orchestration designing stateful, multi-step agent workflows with LangGraph and building chains and tool-use patterns with LangChain
- Observability with tracing, debugging, and monitoring pipeline performance end-to-end with LangSmith and catching retrieval and reasoning failures before they reach users
- Model evaluation and tuning with RAGAS-based evaluation frameworks, benchmarking retrieval recall and answer faithfulness, iterating toward production quality
- Open-weight LLM deployment evaluating and shipping models under memory and latency budgets via Amazon Bedrock and self-hosted inference
- Workflow orchestration with async pipeline design using Temporal.io and containerised deployment on Kubernetes via GitLab CI
Requirements
- Strong software engineering skills in .NET and/or Python with experience building production-grade APIs and services
- Applied algorithmic problem solving including search, ranking, clustering, and data extraction/transformation pipelines
- Solid understanding of LLM architectures and trade-offs such as GPT-family, Claude, Llama, and similar models
- Experience integrating LLM and agent APIs such as Azure OpenAI, OpenAI API, Claude API, Amazon Bedrock
- Design and implementation of agent-based systems for automation, orchestration, and decision support
- Experience working with relational, document, and graph databases including data modeling and querying
- Web data ingestion experience including web scraping, schema extraction, and handling changing source structures
- Experience building reliable, scalable, maintainable AI systems including logging, error handling, and performance considerations
Nice-to-have
- Fine-tuning and preference optimization techniques such as supervised fine-tuning, RL-style approaches via APIs
- Designing pipelines that convert unstructured data into reliable structured representations
- Exposure to event-driven or background processing architectures for long-running AI workflows
- Experience contributing to or operating AI-powered systems in production
How to apply
You can submit your application on the company's website, which you can access by clicking the „Apply on company page“ button.
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