Principal Solutions Architect; Professional Services – AI & Deployment

About Arango

At Arango, we believe the first generation of enterprise AI missed something essential: context. LLM models are powerful, but they don't understand the context needed to deliver accurate answers.

Arango provides a trusted data foundation for the next wave of Enterprise AI with graph-based Contextual AI — transforming enterprise data into a System of Context that truly represents the business, so LLMs can deliver better outcomes with unlimited scale and cost efficiency.

The Arango AI Data Platform gives developers a single, integrated environment to build and scale AI-powered applications without the complexity of stitching together multiple databases and tools. At its core is a massively scalable multi-model database that unifies graph, vector, document, and key‑value data with full-text, geospatial, and vector search — creating the System of Context, the bridge between enterprise data and LLMs.

We’re a global team based in California and Cologne, united by curiosity, collaboration, and a passion for helping developers, data engineers, and technology leaders innovate faster and smarter with AI. Trusted by NVIDIA, HPE, the London Stock Exchange, the U.S. Air Force, NIH, and Articul8, Arango powers enterprise AI with context, confidence, and scale. We are a proud member of the NVIDIA Inception Program and the AWS ISV Accelerate Program.

If you’re excited about shaping the future of Contextual AI, come build with us.

The Principal Solutions Architect – AI & Deployment plays a key role in helping customers deploy, operate, and scale our platform across both on‑premises and cloud environments. This position blends deep technical expertise with strong customer engagement skills to ensure successful Proof‑of‑Concepts (PoCs), smooth production deployments, and long‑term platform adoption. You’ll work closely with Engineering, Product, and Professional Services teams to deliver predictable, repeatable, and high‑quality deployment experiences.

• Lead deployments of self‑managed, Kubernetes‑based environments across on‑prem and cloud infrastructures
• Guide customers through environment readiness, hardware sizing, networking, and configuration requirements
• Install and configure operators, licenses, and supporting platform components
• Partner with Product, Engineering, and Professional Services to clarify requirements, success criteria, and deployment patterns
• Plan and execute PoCs, including scoping, milestones, communication cadence, and technical validation
• Conduct architecture reviews focused on scalability, reliability, security, and operational best practices
• Troubleshoot installation, orchestration, and runtime issues across Kubernetes, containers, and distributed systems
• Develop and maintain deployment guides, runbooks, reference architectures, and best‑practice documentation
• Support customer demos and technical walkthroughs using real or representative datasets
  
  Manage expectations around performance, reliability, and operational boundaries throughout the engagement lifecycle
• Maintain clear engagement plans, status updates, and decision logs to ensure alignment across teams

• 15+ years of experience building, creating complex solutions
• Hands‑on experience deploying and operating software on Kubernetes (on‑prem and cloud)
• Strong Linux fundamentals and experience with containerization technologies
• Experience sizing and configuring environments for data‑intensive or distributed systems
• Familiarity with distributed databases; graph or multi‑model database experience is a plus
• Strong communication skills with the ability to lead technical discussions and guide customers through complex decisions
• Proven ability to troubleshoot performance, capacity, and operational issues in production‑grade environments
• Experience running PoCs end‑to‑end, including planning, execution, and success measurement
• Comfortable using modern collaboration tools (Click Up, Slack, etc.)

• Experience with AI/ML workflows, RAG/Graph
  
  RAG, vector search, or agent‑based architectures
• Background in Professional Services, customer‑facing engineering, or deployment…