AI Solution Architect

Overview

Job Description

Responsibilities

• - Design, build, and maintain sophisticated LangGraph ReAct agents, orchestrating tools across knowledge graphs, vector search, and relational data.
• - Architect and optimize end-to-end RAG pipelines, including embedding strategies, hybrid search, Reciprocal Rank Fusion, and reranking.
• - Develop and evaluate system prompts for complex tasks such as code analysis, entity/field comparison, and cross-file synthesis.
• - Design and implement batch LLM workflows for data model comparisons and aggregate analysis, ensuring robustness and efficiency.
• - Integrate AI functionalities deeply with Neo4j graph data, ensuring efficient graph queries and fluent data flow.
• - Provide technical leadership, contributing to architecture, PR strategies, and mentoring the team on LLM best practices.

Required Skills

• - 5+ years in applied ML/AI engineering with 2+ years building production LLM systems.
• - Deep experience with multi-agent orchestration frameworks (LangChain, LangGraph), including tool calling and state management.
• - Proven expertise in designing and tuning RAG systems, understanding embedding models, vector databases, and chunking.
• - Strong Python skills, specifically with FastAPI and asyncio, for building production services.
• - Demonstrated ability in prompt engineering for classification, extraction, and synthesis, and LLM evaluation using patterns like LLM-as-judge.

Benefits

• - Attractive salary
• - Large freedom and real influence
• - No unhealthy competition, team approach to meeting challenges
• - Remote-first, flexible working culture
• - Company apartments in cool cities across Europe: work and enjoy a memorable getaway