AlphaSense is looking for Cloud Support Engineer

AlphaSense is hiring Cloud Support Engineers in Delhi for its global cloud operations and technical support teams. This is an excellent opportunity for professionals seeking high-paying Cloud Support Engineer jobs in India, AWS Cloud Engineer careers, Kubernetes Support Engineer roles, Site Reliability Engineering (SRE) opportunities, SaaS Support Engineer jobs, and Cloud Operations careers in AI-powered enterprise technology environments.

AlphaSense is trusted by over 6,000 enterprise customers worldwide, including leading Fortune 500 companies, delivering AI-powered market intelligence and cloud-based analytics solutions. The company works with advanced cloud technologies, large-scale distributed systems, Kubernetes infrastructure, observability platforms, AI-driven workflows, and enterprise SaaS applications.

This role is ideal for professionals passionate about AWS Cloud Infrastructure, Kubernetes, Cloud Support Engineering, Technical Troubleshooting, Observability Platforms, API Troubleshooting, AI-powered Operations, and Site Reliability Engineering.

Candidates will work closely with engineering, customer support, DevOps, and R&D teams to resolve cloud infrastructure challenges, improve customer experiences, automate workflows, and support mission-critical SaaS platforms.

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Key Skills Required

• Strong knowledge of AWS cloud services and cloud operations
• Hands-on experience with Kubernetes and Docker environments
• Proficiency with CLI tools such as kubectl and awscli
• Strong scripting skills in Python, JavaScript, or similar languages
• Understanding of GraphQL and REST APIs
• Knowledge of SaaS platform troubleshooting and cloud support
• Experience with monitoring and observability tools like Prometheus and Grafana
• Familiarity with incident response and root cause analysis
• Understanding of logging systems and infrastructure monitoring
• Exposure to Infrastructure as Code (IaC) tools like Crossplane
• Knowledge of networking and distributed systems troubleshooting
• Familiarity with databases such as MongoDB, MySQL, and Elasticsearch
• Strong customer communication and problem-solving skills
• AI fluency and experience using AI tools for investigations and automation

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Roles & Responsibilities

• Provide advanced technical support for SaaS and private cloud environments
• Investigate, diagnose, and resolve cloud infrastructure issues
• Act as the second line of defense for customer technical queries
• Troubleshoot Kubernetes, AWS, API, and infrastructure-related incidents
• Analyze logs, traces, alerts, and monitoring metrics
• Work with kubectl, awscli, and scripting tools for issue resolution
• Collaborate with Engineering, R&D, and Support teams across regions
• Escalate complex issues with detailed technical artifacts and RCA findings
• Maintain and improve runbooks, KEDB articles, and technical documentation
• Support customer onboarding and cloud platform troubleshooting
• Utilize AI tools for log analysis, technical investigations, and documentation
• Build reusable AI workflows and operational automation practices
• Advocate for customer needs and platform reliability improvements
• Contribute to cloud operations, observability, and service optimization initiatives

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What We Offer

• Opportunity to work with a globally recognized AI-driven technology company
• Exposure to advanced cloud-native and Kubernetes environments
• Career growth into Senior Cloud Support Engineer and SRE roles
• Experience with enterprise-scale SaaS platforms and distributed systems
• Hands-on exposure to AI-powered operational workflows
• Collaborative global engineering and support culture
• Learning opportunities across cloud infrastructure and DevOps technologies
• Opportunity to work with modern observability and monitoring platforms
• Exposure to cutting-edge AI and cloud transformation technologies
• Structured training and collaboration with engineering teams

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About Company

AlphaSense is a leading AI-powered market intelligence and cloud technology company trusted by thousands of global enterprises and a majority of the S&P 500.

The company provides advanced AI search, cloud analytics, market intelligence, and enterprise SaaS solutions that help organizations make smarter business decisions using trusted public and private content sources.

AlphaSense leverages Artificial Intelligence, Cloud Infrastructure, Distributed Systems, Kubernetes, SaaS Platforms, Observability Systems, and Data Engineering technologies to deliver scalable enterprise solutions globally.

The company continues to expand rapidly following the acquisition of Tegus, strengthening its AI-driven research and cloud technology ecosystem.

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Eligibility Criteria

• Bachelor’s degree in Computer Science, IT, or related field
• 2–4 years of experience in cloud support, IT operations, or technical support
• Strong knowledge of AWS cloud services and Kubernetes
• Experience with scripting languages like Python or JavaScript
• Familiarity with REST APIs and GraphQL troubleshooting
• Knowledge of monitoring and logging tools
• Experience handling customer technical support cases
• Strong troubleshooting and communication skills
• Interest in AI-driven operations and cloud automation

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Recommended Certifications

• AWS Certified Solutions Architect
• AWS Certified SysOps Administrator
• Certified Kubernetes Administrator (CKA)
• Certified Kubernetes Application Developer (CKAD)
• Google Cloud Associate Engineer
• Prometheus Certified Associate
• Docker Certified Associate
• CompTIA Network+
• DevOps Foundation Certification
• Elastic Certified Engineer

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Frequently Asked Questions (Interview Preparation)

1. What cloud platform is primarily used in this role?

AWS is the primary cloud platform used.

2. Is Kubernetes experience mandatory?

Yes, hands-on Kubernetes troubleshooting experience is highly preferred.

3. What scripting languages are important?

Python and JavaScript are commonly used for automation and troubleshooting.

4. What interview topics can be expected?

• AWS cloud troubleshooting
• Kubernetes and Docker concepts
• REST API and GraphQL troubleshooting
• Linux administration
• Networking fundamentals
• Monitoring and observability tools
• Incident response and RCA scenarios
• AI workflows and automation concepts

5. Is this role customer-facing?

Yes, candidates will work closely with enterprise customers and internal engineering teams.

6. Are AI tools used in daily operations?

Yes, AI tools are actively used for investigations, documentation, automation, and operational workflows.

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Career Opportunities

This role can lead to advanced positions such as:

• Senior Cloud Support Engineer
• Site Reliability Engineer (SRE)
• DevOps Engineer
• Cloud Operations Engineer
• Kubernetes Engineer
• Platform Reliability Engineer
• Infrastructure Support Engineer
• Cloud Automation Engineer
• Technical Account Engineer
• Observability Engineer

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