Database and AI Support Engineer

• Provide advanced technical support for database, AI, cloud, Kubernetes, and infrastructure-related customer issues.

• Diagnose complex technical problems by analyzing logs, system behavior, configurations, networking conditions, and other available evidence.

• Investigate database performance and reliability issues involving data modeling, query optimization, indexing, replication, clustering, backups, and performance tuning.

• Troubleshoot Kubernetes environments, including AKS, EKS, OpenShift, Helm deployments, ingress controllers, service endpoints, and cluster administration workflows.

• Analyze infrastructure and networking issues involving load balancers, timeouts, DNS, storage, connectivity, and service endpoints.

• Support environments using AWS, Azure, on-premises infrastructure, Linux, Docker, and related cloud-native technologies.

• Work with storage technologies such as EBS, gp3, MinIO, and S3-compatible storage.

• Apply knowledge of LLMs, embeddings, vector search, RAG, prompt engineering, and AI APIs when diagnosing or supporting AI-enabled applications.

• Use REST APIs, JSON, authentication mechanisms, and scripting with Python, Bash, or similar tools to investigate and resolve issues.

• Read and understand application code to assist with technical troubleshooting and identify potential product defects.

• Collaborate with Engineering, Product, QA, and Customer Success teams to escalate issues, communicate findings, and drive effective resolutions.

• Document solutions, troubleshooting procedures, and technical findings to strengthen internal knowledge bases and improve future support efficiency.

• Build customer trust through clear communication, thoughtful expectation management, and a structured approach to understanding the underlying issue before troubleshooting.

Requirements

• 5+ years of professional experience in Support Engineering or a closely related technical support role.

• At least 3 years of hands-on experience working with databases, preferably including ArangoDB, Neo4j, or comparable database technologies.

• Strong understanding of database fundamentals, including data modeling, query optimization, indexing, clustering, replication, backups, and performance tuning.

• Strong Kubernetes experience, including platforms such as AKS, EKS, or OpenShift, along with Helm.

• Solid understanding of cloud infrastructure, particularly AWS and Azure, as well as on-premises environments.

• Familiarity with storage systems including EBS, gp3, MinIO, and S3-compatible storage.

• Ability to troubleshoot networking issues involving load balancers, timeouts, DNS, service endpoints, and ingress controllers.

• Comfortable working with Linux, SSH, jump boxes, and cluster administration workflows.

• Basic scripting capabilities and familiarity with Python, Bash, or similar scripting languages.

• Ability to read and understand software code and use that knowledge to support technical investigations.

• Understanding of AI and RAG concepts, including LLMs, embeddings, vector search, prompt engineering, and AI APIs.

• Familiarity with REST APIs, JSON, and authentication mechanisms.

• Strong analytical and critical-thinking skills, with the ability to break complex problems into manageable steps and identify root causes objectively.

• Excellent communication skills, with the ability to explain complex technical concepts clearly to technical and non-technical audiences.

• Strong customer orientation, including empathy, expectation management, and the ability to establish trust during challenging technical situations.

• Collaborative mindset and ability to work effectively with Engineering, Product, QA, Customer Success, and other cross-functional teams.

• Fluent written and spoken English.

Benefits

• Fully remote position for candidates based in India.

• Opportunity to work at the intersection of AI, databases, and cloud-native infrastructure.

• Exposure to cutting-edge technologies supporting enterprise AI applications and intelligent systems.

• Opportunity to work with experienced engineering, product, and business professionals.

• Cross-functional collaboration with Engineering, Product, QA, and Customer Success teams.

• Opportunity to solve complex technical challenges and develop expertise across databases, Kubernetes, cloud infrastructure, and AI technologies.

• Opportunity to contribute to the evolution of infrastructure supporting AI-powered applications.