Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform)
IBM
Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform)
Job Description
Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform)
📋 Job Overview
As a Software Engineer on the Quality Engineering and Performance team at IBM, you will develop and evolve system-level testing frameworks for Astra Serverless, a distributed, scalable, serverless NoSQL platform. Your role involves designing automation and frameworks to validate the platform's performance, reliability, and correctness under complex multi-cloud environments and AI-driven workloads.
📍 Location: BANGALORE, IN (Remote/Hybrid)
💼 Career Level: Professional
🎯 Key Responsibilities
- Design and develop frameworks for end-to-end and chaos testing of distributed, serverless Cassandra-based systems
- Engineer automation that validates data correctness, fault tolerance, and performance under complex multi-region and multi-cloud topologies
- Collaborate closely with feature development teams to model real-world scenarios and integrate automated validation into the delivery pipeline
- Continuously evolve the test infrastructure for scale, speed, and observability -- leveraging Kubernetes, Docker, and cloud-native toolchains
- Profile and tune distributed workloads to uncover systemic bottlenecks and verify that service-level goals are consistently met
- Contribute code to shared testing frameworks and participate in design and code reviews across teams
- Own the full cycle of quality engineering -- from test design and execution to insights and continuous improvement
✅ Required Qualifications
- Exposure to system level Java and Python development in testing for distributed or cloud systems -- replication, partitioning, consistency, and eventual convergence
- Familiarity with Linux, Kubernetes, Docker, and CI/CD pipelines (Jenkins, GitHub Actions, etc.)
- Knowledge of analyzing complex logs and metrics to isolate performance and reliability issues
⭐ Preferred Qualifications
- Eagerness to learn more about and using chaos testing, fault injection, or resilience validation
- Familiarity with NoSQL technologies (Cassandra, DynamoDB, ScyllaDB, etc.) and cloud platforms (AWS, GCP, Azure) and multi-cloud topologies
- Understanding of vector search, AI embeddings, or data-intensive workloads
- Curiosity-driven mindset, strong communication skills, and a focus on collaboration and craftsmanship
🛠️ Required Skills
- Java
- Python
- Linux
- Kubernetes
- Docker
- CI/CD pipelines
- Jenkins
- GitHub Actions
- Log analysis
- Metrics analysis
- Chaos testing
- Fault injection
- Resilience validation
- NoSQL technologies
- Cassandra
- DynamoDB
- ScyllaDB
- Cloud platforms
- AWS
- GCP
- Azure
- Multi-cloud topologies
- Vector search
- AI embeddings
- Data-intensive workloads
- Curiosity
- Communication
- Collaboration
- Craftsmanship
🎁 Benefits & Perks
- Opportunity to learn and develop career
- Encouragement to be courageous and experiment
- Continuous trust and support in an inclusive environment
- Growth-minded culture with openness to feedback and learning
- Opportunity to collaborate and drive exceptional outcomes for customers
Locations
- BANGALORE, IN, India (Remote)
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Javaintermediate
- Pythonintermediate
- Linuxintermediate
- Kubernetesintermediate
- Dockerintermediate
- CI/CD pipelinesintermediate
- Jenkinsintermediate
- GitHub Actionsintermediate
- Log analysisintermediate
- Metrics analysisintermediate
- Chaos testingintermediate
- Fault injectionintermediate
- Resilience validationintermediate
- NoSQL technologiesintermediate
- Cassandraintermediate
- DynamoDBintermediate
- ScyllaDBintermediate
- Cloud platformsintermediate
- AWSintermediate
- GCPintermediate
- Azureintermediate
- Multi-cloud topologiesintermediate
- Vector searchintermediate
- AI embeddingsintermediate
- Data-intensive workloadsintermediate
- Curiosityintermediate
- Communicationintermediate
- Collaborationintermediate
- Craftsmanshipintermediate
Required Qualifications
- Exposure to system level Java and Python development in testing for distributed or cloud systems -- replication, partitioning, consistency, and eventual convergence (experience)
- Familiarity with Linux, Kubernetes, Docker, and CI/CD pipelines (Jenkins, GitHub Actions, etc.) (experience)
- Knowledge of analyzing complex logs and metrics to isolate performance and reliability issues (experience)
Preferred Qualifications
- Eagerness to learn more about and using chaos testing, fault injection, or resilience validation (experience)
- Familiarity with NoSQL technologies (Cassandra, DynamoDB, ScyllaDB, etc.) and cloud platforms (AWS, GCP, Azure) and multi-cloud topologies (experience)
- Understanding of vector search, AI embeddings, or data-intensive workloads (experience)
- Curiosity-driven mindset, strong communication skills, and a focus on collaboration and craftsmanship (experience)
Responsibilities
- Design and develop frameworks for end-to-end and chaos testing of distributed, serverless Cassandra-based systems
- Engineer automation that validates data correctness, fault tolerance, and performance under complex multi-region and multi-cloud topologies
- Collaborate closely with feature development teams to model real-world scenarios and integrate automated validation into the delivery pipeline
- Continuously evolve the test infrastructure for scale, speed, and observability -- leveraging Kubernetes, Docker, and cloud-native toolchains
- Profile and tune distributed workloads to uncover systemic bottlenecks and verify that service-level goals are consistently met
- Contribute code to shared testing frameworks and participate in design and code reviews across teams
- Own the full cycle of quality engineering -- from test design and execution to insights and continuous improvement
Benefits
- general: Opportunity to learn and develop career
- general: Encouragement to be courageous and experiment
- general: Continuous trust and support in an inclusive environment
- general: Growth-minded culture with openness to feedback and learning
- general: Opportunity to collaborate and drive exceptional outcomes for customers
Tags & Categories
Answer 10 quick questions to check your fit for Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform) @ IBM.
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Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform)
IBM
Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform)
Job Description
Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform)
📋 Job Overview
As a Software Engineer on the Quality Engineering and Performance team at IBM, you will develop and evolve system-level testing frameworks for Astra Serverless, a distributed, scalable, serverless NoSQL platform. Your role involves designing automation and frameworks to validate the platform's performance, reliability, and correctness under complex multi-cloud environments and AI-driven workloads.
📍 Location: BANGALORE, IN (Remote/Hybrid)
💼 Career Level: Professional
🎯 Key Responsibilities
- Design and develop frameworks for end-to-end and chaos testing of distributed, serverless Cassandra-based systems
- Engineer automation that validates data correctness, fault tolerance, and performance under complex multi-region and multi-cloud topologies
- Collaborate closely with feature development teams to model real-world scenarios and integrate automated validation into the delivery pipeline
- Continuously evolve the test infrastructure for scale, speed, and observability -- leveraging Kubernetes, Docker, and cloud-native toolchains
- Profile and tune distributed workloads to uncover systemic bottlenecks and verify that service-level goals are consistently met
- Contribute code to shared testing frameworks and participate in design and code reviews across teams
- Own the full cycle of quality engineering -- from test design and execution to insights and continuous improvement
✅ Required Qualifications
- Exposure to system level Java and Python development in testing for distributed or cloud systems -- replication, partitioning, consistency, and eventual convergence
- Familiarity with Linux, Kubernetes, Docker, and CI/CD pipelines (Jenkins, GitHub Actions, etc.)
- Knowledge of analyzing complex logs and metrics to isolate performance and reliability issues
⭐ Preferred Qualifications
- Eagerness to learn more about and using chaos testing, fault injection, or resilience validation
- Familiarity with NoSQL technologies (Cassandra, DynamoDB, ScyllaDB, etc.) and cloud platforms (AWS, GCP, Azure) and multi-cloud topologies
- Understanding of vector search, AI embeddings, or data-intensive workloads
- Curiosity-driven mindset, strong communication skills, and a focus on collaboration and craftsmanship
🛠️ Required Skills
- Java
- Python
- Linux
- Kubernetes
- Docker
- CI/CD pipelines
- Jenkins
- GitHub Actions
- Log analysis
- Metrics analysis
- Chaos testing
- Fault injection
- Resilience validation
- NoSQL technologies
- Cassandra
- DynamoDB
- ScyllaDB
- Cloud platforms
- AWS
- GCP
- Azure
- Multi-cloud topologies
- Vector search
- AI embeddings
- Data-intensive workloads
- Curiosity
- Communication
- Collaboration
- Craftsmanship
🎁 Benefits & Perks
- Opportunity to learn and develop career
- Encouragement to be courageous and experiment
- Continuous trust and support in an inclusive environment
- Growth-minded culture with openness to feedback and learning
- Opportunity to collaborate and drive exceptional outcomes for customers
Locations
- BANGALORE, IN, India (Remote)
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Javaintermediate
- Pythonintermediate
- Linuxintermediate
- Kubernetesintermediate
- Dockerintermediate
- CI/CD pipelinesintermediate
- Jenkinsintermediate
- GitHub Actionsintermediate
- Log analysisintermediate
- Metrics analysisintermediate
- Chaos testingintermediate
- Fault injectionintermediate
- Resilience validationintermediate
- NoSQL technologiesintermediate
- Cassandraintermediate
- DynamoDBintermediate
- ScyllaDBintermediate
- Cloud platformsintermediate
- AWSintermediate
- GCPintermediate
- Azureintermediate
- Multi-cloud topologiesintermediate
- Vector searchintermediate
- AI embeddingsintermediate
- Data-intensive workloadsintermediate
- Curiosityintermediate
- Communicationintermediate
- Collaborationintermediate
- Craftsmanshipintermediate
Required Qualifications
- Exposure to system level Java and Python development in testing for distributed or cloud systems -- replication, partitioning, consistency, and eventual convergence (experience)
- Familiarity with Linux, Kubernetes, Docker, and CI/CD pipelines (Jenkins, GitHub Actions, etc.) (experience)
- Knowledge of analyzing complex logs and metrics to isolate performance and reliability issues (experience)
Preferred Qualifications
- Eagerness to learn more about and using chaos testing, fault injection, or resilience validation (experience)
- Familiarity with NoSQL technologies (Cassandra, DynamoDB, ScyllaDB, etc.) and cloud platforms (AWS, GCP, Azure) and multi-cloud topologies (experience)
- Understanding of vector search, AI embeddings, or data-intensive workloads (experience)
- Curiosity-driven mindset, strong communication skills, and a focus on collaboration and craftsmanship (experience)
Responsibilities
- Design and develop frameworks for end-to-end and chaos testing of distributed, serverless Cassandra-based systems
- Engineer automation that validates data correctness, fault tolerance, and performance under complex multi-region and multi-cloud topologies
- Collaborate closely with feature development teams to model real-world scenarios and integrate automated validation into the delivery pipeline
- Continuously evolve the test infrastructure for scale, speed, and observability -- leveraging Kubernetes, Docker, and cloud-native toolchains
- Profile and tune distributed workloads to uncover systemic bottlenecks and verify that service-level goals are consistently met
- Contribute code to shared testing frameworks and participate in design and code reviews across teams
- Own the full cycle of quality engineering -- from test design and execution to insights and continuous improvement
Benefits
- general: Opportunity to learn and develop career
- general: Encouragement to be courageous and experiment
- general: Continuous trust and support in an inclusive environment
- general: Growth-minded culture with openness to feedback and learning
- general: Opportunity to collaborate and drive exceptional outcomes for customers
Tags & Categories
Answer 10 quick questions to check your fit for Software Engineer - Quality and Performance – Distributed Systems (Serverless NoSQL Platform) @ IBM.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs