Customer Solution Architect — Arango AI Product Suite

Location: Anywhere in the United Kingdom / Remote

Company

Builds a unified multimodel contextual data platform connecting enterprise data with LLMs, copilots, and AI agents through graph, vector, document, key-value, and search capabilities.

What you will do

• Own the technical customer relationship from discovery and solution design through pilots, production deployment, and expansion.
• Design multimodel architectures with graph schemas, AQL queries and traversals, knowledge graphs, and GraphRAG retrieval.
• Build reference implementations, data connectors, GraphRAG pipelines, APIs, and tool or agent orchestration prototypes.
• Guide secure, observable production deployments with CI/CD, infrastructure as code, testing, monitoring, alerting, and dashboards.
• Develop hybrid retrieval, evaluation, data pipelines, vector indices, governance, guardrails, and compliance controls.
• Document architectures and runbooks, train customer teams, and provide field feedback to product and engineering.

Requirements

• Deep hands-on expertise in graph data modeling, graph queries and traversal, graph algorithms, knowledge graphs, and GraphRAG for LLM applications.
• 5+ years of experience in software engineering, solution architecture, or technical professional services building and operating production systems.
• Strong applied AI and Python skills, including systems design, concurrency, networking, and modern LLM tooling.
• Experience with graph, NoSQL, key-value, document, vector, and retrieval databases, including hybrid graph and vector retrieval.
• Experience with AWS, GCP, or Azure; Docker, Kubernetes, Terraform or CloudFormation, and CI/CD.
• Excellent customer-facing communication, from executive-level architecture discussions to engineering design reviews.

Nice to have

• hirify.globalDB or production graph database experience.
• Search and information retrieval expertise, including BM25, reranking, ColBERT, or cross-encoders.
• Front-end or full-stack experience with TypeScript, React, or Next.js.
• MLOps, evaluation frameworks, model adaptation, inference optimization, or security and compliance experience.
• Experience in finance, healthcare, public sector, manufacturing, retail, or French government and industry.

Culture & Benefits

• Work on AI and data infrastructure for enterprise applications.
• Collaborate with experienced engineering, marketing, and product teams.
• Contribute to the development of a contextual data layer for AI-powered applications.
• Help shape product and engineering direction through customer and field feedback.