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Open nowPosted 4 hours agoWe saw it 56 min after it went up

Database and AI Support Engineer

Jobgether3,695 open roles

Where
India
Work mode
Remote
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Your applicationOpen nowDatabase and AI Support EngineerJobgether · India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Jobgether's own form.

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. Jobgether postings stay open a median of 4 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.4%3 days
  3. 7.8%7 days
  4. 14.3%14 days
  5. 33.7%30 days
This job: posted 4 hours ago

Jobgether median: 4 days open

The posting

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Database and AI Support Engineer based in India.

This is an experienced technical support role focused on databases, cloud infrastructure, and modern AI systems. You will help customers troubleshoot complex database, Kubernetes, networking, and infrastructure challenges in production environments. The role combines deep database expertise with practical knowledge of LLMs, embeddings, vector search, and retrieval-augmented generation. You will investigate technical issues, analyze logs, identify root causes, and work closely with Engineering and Product teams to resolve complex problems. You will also contribute to customer success by translating technical concepts into clear, actionable guidance for both technical and non-technical audiences. The position offers exposure to multimodel data technologies, cloud-native infrastructure, and the evolving foundations of enterprise AI. This remote opportunity is suited to a collaborative problem-solver who enjoys technical ownership, customer interaction, and working at the intersection of data and AI.

Accountabilities

  • 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.
  • 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.
  • 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.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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