We are looking for an experienced Senior AI Engineer on behalf of a leading global SaaS enterprise. In this assignment, you will join an autonomous innovation team focused on building next-generation grounding and retrieval infrastructure for enterprise AI applications. The primary mission centers on architecting knowledge graphs and retrieval-augmented generation (RAG) frameworks to transform structured technical content into verifiable ground truth for large-scale AI deployments.

Assignment Description
The objective of this assignment is to design, implement, and scale end-to-end RAG retrieval pipelines and knowledge graph structures that elevate answer accuracy and retrieval quality for enterprise AI implementations. You will take ownership of key architectural decisions spanning graph representations, vector databases, chunking strategies, embeddings, hybrid retrieval, re-ranking, and evaluation frameworks. Working directly with key clients, you will turn complex requirements into production-ready AI grounding capabilities while optimizing for retrieval precision, latency, token economics, and hallucination reduction. Additionally, you will establish core architectural foundations and align implementations with enterprise security standards and data protection obligations.

Requirements and Preferred Qualifications

Mandatory requirements:

5+ years of experience as a software engineer with significant full-stack development experience.

2+ years of proven experience delivering production-grade AI features to market.

Direct experience building RAG architectures, working with vector databases, embeddings, and executing retrieval evaluations.

Strong working knowledge of knowledge graphs, graph databases, or structured retrieval techniques, combined with sound judgement regarding when graph-based retrieval outperforms vector search.

Solid technical skills in TypeScript, Python, backend architecture, containerization, infrastructure-as-code, and cloud infrastructure with AWS preferred.

Familiarity with agentic workflows and tool integrations using protocols such as MCP.

Demonstrated product sense to effectively balance trade-offs between retrieval quality, latency, and cost.

Full professional fluency in English.

Current residence in Sweden alongside valid legal right to work.

Nice to have:

Experience handling multilingual or structured and semi-structured content at enterprise scale.

Familiarity with the Rust programming language.

Prior experience working within a SaaS business model.

Start
ASAP

Location
Stockholm, Sweden.

Remote/Office Policy
Hybrid setup based out of the Stockholm office.