What are the responsibilities and job description for the Principal Solutions Architect (Professional Services) – AI & Deployment position at Arango?
About The Role
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.
Key Responsibilities
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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.
Key Responsibilities
- 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 (ClickUp, Slack, etc.)
- Experience with AI/ML workflows, RAG/GraphRAG, vector search, or agent‑based architectures
- Background in Professional Services, customer‑facing engineering, or deployment engineering
- Knowledge of licensing models, key management, or enterprise security practices
- Experience with distributed systems, NoSQL databases, or multi‑model data platforms
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