Golang/Kubernetes Engineer
Boost your chances before you apply.
Arango
US
Summary
Lead the design and development of the ArangoDB Kubernetes Operator to ensure robust lifecycle management, scaling, and replication. Collaborate with engineering teams to define best practices for stateful systems and support enterprise-grade cloud deployments.
Job Description
Golang/Kubernetes Engineer
About Arango:
Arango delivers a unified, natively multimodel contextual data platform that powers AI agents, assistants, and applications with the unified, current, and trusted business context needed to reason, decide, and act at scale.
The Arango Contextual Data Platform connects fragmented enterprise data with LLMs, copilots, and AI agents through a simplified architecture delivered out of the box. By combining graph, vector, document, key-value, and search capabilities in a single platform, Arango eliminates the complex stacks many organizations build to operationalize enterprise AI.
Trusted by organizations including NVIDIA, HPE, the London Stock Exchange, PSI CRO, the U.S. Air Force, NIH, Siemens, Transient.AI, Matpriskollen, and Articul8, Arango helps enterprises move from AI pilots to reliable production systems faster while lowering infrastructure complexity and total cost of ownership. Arango is a proud member of the NVIDIA Inception Program and the AWS ISV Accelerate Program. Learn more at arango.ai, LinkedIn, and G2.
Location: Only candidates in the USA will be considered for the role (Remote).
About the Role
We are seeking a Senior Engineer to lead development of the ArangoDB operator, responsible for ensuring robust lifecycle management, scaling, back-up, and replication capabilities for ArangoDB running on Kubernetes. You will shape the architecture of core operator components, design and implement new features, influence best practices for deploying stateful systems on Kubernetes, and ensure that ArangoDB continues to meet enterprise-grade expectations for performance, consistency, and stability. This is an opportunity to own a critical part of our ecosystem and directly impact how modern AI-driven applications run in production.
Responsibilities
- Lead the design and development of the ArangoDB Kubernetes Operator.
- Own core operator architecture and implement features for lifecycle management, scaling, backup, and replication.
- Ensure high availability, performance, and stability of ArangoDB on Kubernetes.
- Define best practices for running stateful systems on Kubernetes.
- Collaborate with engineering teams to align operator capabilities with enterprise and cloud requirements.
- Troubleshoot complex issues across Kubernetes and distributed systems.
- This role supports a U.S. Air Force project and requires U.S. citizenship.
- Support extension of the solution into GovCloud (AWS)
Key Qualifications
- 4+ years of programming and Cloud experience
- Deep expertise in Kubernetes, CRDs and operators (deployments, custom resources like ArangoDeployment, ArangoBackup, ArangoLocalStorage, replication, etc.)
- Strong experience in Go (the operator is written in Go) plus solid understanding of concurrency, storage, and distributed system concerns.
- Strong experience in Cloud solutions, especially AWS. AWS GovCloud is an additional point
- Proven background in designing and managing production-grade distributed databases or stateful systems, including storage management and data replication. (e.g., persistent volumes, snapshot/backup, failover, cluster scaling)
- Familiarity with storage concepts in Kubernetes: PersistentVolumes, PVCs, local storage, volume resizing, storage performance tuning.
- Operational mindset: ability to ensure stability, handle upgrades/migrations, observability/metrics, and manage cluster lifecycle through automation and best practices.
- Strong communication and leadership skills: able to drive technical discussions, review code, mentor contributors, write clear design documents and documentation for both internal and external users.
- U.S. citizenship is required.
- Active security clearance is preferred.
What Makes Arango Special?
At Arango, we believe that AI is only as powerful as the data foundation. Our mission is to help organizations build AI systems that can reason, decide and act based on unified, current, and trusted business context at scale. We are helping define a new category of infrastructure: the contextual data layer for AI.
Working at Arango means:
- Contributing to cutting-edge AI and data infrastructure
- Collaborating with experienced engineers, marketers, and product leaders
- Helping shape how enterprises build AI-powered applications
If you're excited about the intersection of AI, data, and social media, we’d love to hear from you.
Arango provides the trusted data foundation for enterprise AI through its Contextual Data Platform, transforming fragmented enterprise data into a contextual data layer that enables AI systems to operate with business context at scale.
The Arango Contextual Data Platform gives developers a single, integrated environment to build and run AI-powered applications, agents, and assistants without stitching together multiple databases, search systems, and AI infrastructure. It combines a multimodel data foundation—graph, vector, document, and key-value—with built-in search and governance capabilities. This enables AI agents to ground responses in enterprise context, navigate relationships across data types, and take reliable, state-aware actions based on real-time data.
The Arango Agentic AI Suite is the agent layer of the Arango Contextual Data Platform—connecting LLMs to governed enterprise data through contextual retrieval and tool-based execution.
It turns fragmented data into context-rich knowledge graphs using AutoGraph and multi-modal RAG pipelines (GraphRAG, VectorRAG, and HybridRAG), enabling agents to reason over relationships—not just retrieve documents.
Core capabilities include:
→ multimodal ingestion + AutoGraph for automated knowledge graph creation
→ GraphRAG and natural-language querying via AQLizer
→ Graph Visualizer for interactive exploration and explainability
→ Graph Analytics and GraphML for relationship-driven insights
→ integration with LLMs and ML tooling for agent execution
The result: context-aware, governed agent workflows that enable agents to reason, decide, and act with full business context, delivering explainable and auditable outcomes.
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. Learn more at arango.ai, LinkedIn, and YouTube.
Founded
2015
Company size
51-200 employees
Industry
Software Development
Org type
Privately Held
Headquarters
San Francisco, CA
Arango provides the trusted data foundation for enterprise AI through its Contextual Data Platform, transforming fragmented enterprise data into a contextual data layer that enables AI systems to operate with business context at scale.
The Arango Contextual Data Platform gives developers a single, integrated environment to build and run AI-powered applications, agents, and assistants without stitching together multiple databases, search systems, and AI infrastructure. It combines a multimodel data foundation—graph, vector, document, and key-value—with built-in search and governance capabilities. This enables AI agents to ground responses in enterprise context, navigate relationships across data types, and take reliable, state-aware actions based on real-time data.
The Arango Agentic AI Suite is the agent layer of the Arango Contextual Data Platform—connecting LLMs to governed enterprise data through contextual retrieval and tool-based execution.
It turns fragmented data into context-rich knowledge graphs using AutoGraph and multi-modal RAG pipelines (GraphRAG, VectorRAG, and HybridRAG), enabling agents to reason over relationships—not just retrieve documents.
Core capabilities include:
→ multimodal ingestion + AutoGraph for automated knowledge graph creation
→ GraphRAG and natural-language querying via AQLizer
→ Graph Visualizer for interactive exploration and explainability
→ Graph Analytics and GraphML for relationship-driven insights
→ integration with LLMs and ML tooling for agent execution
The result: context-aware, governed agent workflows that enable agents to reason, decide, and act with full business context, delivering explainable and auditable outcomes.
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. Learn more at arango.ai, LinkedIn, and YouTube.
Founded
2015
Company size
51-200 employees
Industry
Software Development
Org type
Privately Held
Headquarters
San Francisco, CA
