Senior AI Engineer
4 tygodni temu
Summary
The primary objective of the Senior AI Engineer role is to enhance the AI capabilities of the GenAI team by advancing the existing Retrieval-Augmented Generation (RAG) engine and implementing complex agent solutions.
Location: Remote (occasional trips to Denmark possible, but not required).
Contract: 6 months with extension
Start Date: Flexible – preferable up to one month notice period
Salary: 180-200 zł/h
Main Responsibilities:
The Senior AI Engineer will primarily focus on the RAG engine and agent solutions, including agent-to-agent orchestration.
Enhance the RAG engine across various stages:
Ingestion: Creating robust pipelines for chunking, metadata enrichment, deduplication, and idempotent updates.
Retrieval: Developing high-quality search mechanisms involving query rewriting, hybrid retrieval, multi-hop, and re-ranking strategies.
Evaluation: Establishing systematic measurement processes using ground-truth datasets to assess RAGAS metrics such as accuracy, latency, and coverage.
Build and improve GenAI agents tailored for real-world applications.
Implement scalable solutions utilizing Python within the Microsoft Azure ecosystem.
Apply agent frameworks, specifically LangGraph and Langfuse, in production environments.
Collaborate with data scientists on machine learning and large language models (ML/LLM) tasks.
Contribute to overall architecture, robustness, and best practices for deployment.
Key Requirements:
Strong background in Python software engineering.
Demonstrated experience with RAG involving ingestion, retrieval, and evaluation in production settings.
Hands-on experience with Docker and containerized deployment.
Proficient with FastAPI, emphasizing best practices for building and maintaining REST APIs.
Experience with Model Context Protocol (MCP), focusing on development and integration of MCP servers and clients.
Familiarity with Azure services (OpenAI, AI Search, Functions, etc.).
Proven capability to develop and maintain solutions in production environments.
Strong knowledge of frameworks like LangGraph (for agents) and Langfuse (for observability).
Nice to Have:
Experience with Kubernetes.
Familiarity with Databricks.
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