Link Group

Agentic AI Engineer

130 - 165 PLN/ godz./ godz.B2BB2B (netto)

SeniorZdalnieFull-time·B2B

#459090·Dodano miesiąc temu·2

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Python SQL GitAIRAGLLM

Podsumowanie oferty

The role focuses on architecting, building, and optimizing autonomous AI agents and associated tool integration frameworks. The position requires expertise in designing advanced Retrieval-Augmented Generation (RAG) pipelines and multi-step agentic workflows. Responsibilities include LLM evaluation, benchmark design, systematic error analysis, and production deployment of LLM applications with observability and performance monitoring. The engineer applies recent AI research directly to software product development.

Wymagania

High proficiency in Python, SQL, and Git version control.
Proven experience in prompt engineering, context engineering, RAG patterns, and designing agent/tool ecosystems.
Hands-on experience with LLM evaluation frameworks, benchmark design, model selection, and systematic error analysis.
Practical experience deploying LLM applications, including observability, tracing, cost monitoring, and latency tuning.
Demonstrated ability to dissect recent AI papers and open-source breakthroughs and apply them directly to software products.

Obowiązki

Agentic Systems & Tool Design:

Architect, build, and optimize autonomous AI agents, tool integration frameworks, skills, and multi-step agentic workflows.

Context Engineering & RAG:

Design and refine advanced Retrieval-Augmented Generation (RAG) pipelines, system prompts, and context-window strategies for maximum accuracy and efficiency.

AI Research & Innovation:

Stay at the forefront of cutting-edge AI/LLM research and translate emerging methodologies into practical product enhancements.

Model Evaluation & Error Analysis:

Conduct systematic model selection, benchmarks, and granular error analysis to continuously improve output quality and mitigate hallucinations.

LLMOps & Observability:

Deploy, monitor, and maintain LLM applications in production; implement telemetry, logging, and performance tracking to ensure system reliability.

Software Engineering:

Write scalable, clean, and maintainable code, maintaining repository best practices and version control workflows.

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