9+ Database performance tuning Jobs in India

AI Product QA Engineer

This is not the QA you know. We're not hiring someone to find bugs. We're hiring someone to guard the user's experience — with AI as the foundation.

Read this before you read anything else

Forget everything traditional QA taught you.

I don't want "I tested it, here are the 14 defects." I don't want a gatekeeper at the end of the line ticking checkboxes against a technical feature list. That QA is dead here, and honestly, AI already does it better.

I want business-product QA. Product taste as a discipline. User empathy as a test case. Your foundation is AI — everything runs through Claude Code / Codex — and on top of that foundation you apply QA from a business, user-empathy, onboarding, and go-to-market lens. You're not asking "does the button work?" You're asking "is this the sharpest user journey this product could possibly have?"

We're extreme about four things and nothing else: extreme hard work, extreme respect, extreme shipping, extreme innovation. Not hours . There's no boss — there's a product, a user, and you. You're rewarded on one thing: your hunger.

The 90 / 10

Same philosophy that runs this whole company. 90% of the work, AI does. Claude Code writes the test cases, automates the suites, drives the API calls, spins up the harness — faster than any QA team I've ever run . That 90% is the floor now.

The 10% is you — the human who decides what's actually worth testing and why:

• the user empathy — feeling the friction a real brand manager feels at 9pm
• the judgment — is this the sharpest journey, or just a working one?
• the taste — the design standard, the elegance, the delight
• the business sense — does this survive a real client's Tuesday, their onboarding, their objection?
• the critical eye — reading an AI trace and knowing instantly when the product is confidently wrong

AI didn't shrink QA. It concentrated it. The 10% is smaller and heavier than the 100% ever was. That's the 10% I'm hiring.

How you actually work

Everything you do runs through Claude Code. You write the cases in it. You automate the cases in it. You do business testing in it. You interrogate user empathy in it — "how will the user react to this, and is this the sharpest journey of the product?"

But make no mistake: this is technical QA. You write scripts. You hit and test APIs directly. You read the traces, the payloads, the failure modes. You don't wait for a UI to click — you go straight at the system. The difference from old-school QA isn't less technical; it's technical in service of the user and the business, not the feature checklist.

The stack & the surface

We're a web application in Python, Rust, and everything in between — and you'll be QA-ing across four products: ARIA, the Persona product, the video-decoding product, and the rest of the family. Real APIs, real pipelines, real agents watching millions of social videos in Hindi, Tamil, Bahasa, Thai for the world's biggest consumer brands . You need to be comfortable writing a script to probe any of them and reading exactly what came back.

Your first 48 hours

Day one, morning: you get access to a live product and its real client questions in the queue. Not a sandbox. Not a tutorial.

Day one, afternoon: you pick one user journey and, in Claude Code, you build the case, automate it, and pressure-test it against the actual experience a client would have.

Day two: you tell me not "here are the defects" but "here's where the journey breaks the user, and here's the sharper one." And you've already got the automated eval that guards it going forward.

If that scares you, this isn't your room. If it makes you grin — keep reading.

The loop

We are always on. A technique drops on Twitter Tuesday morning; by Thursday it's in a product; by Friday a brand team on the other side of the world is using it — and someone has to make sure that journey is delightful, not just functional. That someone is you. See it. Test it against the user. Sharpen it. Ship it. The loop never stops. If your learning lives in "read later" folders , this will break you.

What you own

The user's experience across every product. Not the defect list — the journey. Find a problem and you don't just log the instance; you build the automated eval in Claude Code that kills the whole class of bad experience forever. Your evals become the product's conscience. Your standard becomes the bar the whole team ships to.

The bar is craft, not years. 23 or 43 — I don't care. I care whether you can feel what a user feels and write the script that proves it.

Who this is actually for

This is a close-to-100% self-starter environment.

You do not want to be here if you want to be handed a test plan. You want to be here if you believe you're the only one who can guard this product's soul — the king or queen of the user journey — with absolute hunger burning in you to do it. Here, will is bigger than skill. And AI isn't a tool you use; it's the foundation you think on.

Fair warning ⚠

The pace is relentless and there's no playbook for AI-product QA — you're partly inventing the discipline as you go. If you want a stable checklist and a comfortable gate at the end of the pipeline, you'll be miserable here, and I'd rather you know now. But if you want to define what QA even means in the age of agents — what you learn here in one year, you won't learn anywhere else in five.

How this goes

Don't send a resume. Send the 10%.

An eval harness you're proud of. A test suite you built in Claude Code that caught something a checklist never would. A teardown of a product's user journey where your taste and your technical chops were unmistakably yours.

Work Location: Remote

Applicants must read the JD and understand the JD throughly

Job Title: Database & DevOps Engineer

Location: Chennai, Tamil Nadu (On-site/Hybrid)

Experience: 2+ years -

Job Summary

We are looking for a skilled Database & DevOps Engineer with 2+ years of hands-on experience in database administration, cloud infrastructure, CI/CD pipelines, automation, and AI application deployment. The role involves managing database and infrastructure environments, automating deployments, supporting AI/LLM workloads, and ensuring high availability, security, performance, and scalability.

Key Responsibilities

Database Management

• Install, configure, monitor, and maintain SQL and NoSQL databases.

• Manage database backup, recovery, replication, and disaster recovery.

• Optimise performance through indexing, query tuning, and monitoring.

• Ensure database security, integrity, and availability.

• Troubleshoot database issues and provide timely resolutions.

DevOps, Infrastructure & AI Operations

• Design, implement, and maintain CI/CD pipelines.

• Automate infrastructure provisioning using Infrastructure as Code tools.

• Deploy and manage applications across cloud and on-premises environments.

• Configure and maintain containerised applications using Docker and Kubernetes.

• Deploy and support AI/ML, LLM, RAG, and agentic AI applications.

• Configure and manage GPU-enabled infrastructure for AI workloads.

• Support model serving, vector databases, and AI application APIs.

• Monitor application, infrastructure, and AI-service performance, including availability, latency, resource utilization, and failures.

• Maintain Linux servers and automate routine operational tasks.

• Implement secure management of credentials, secrets, model endpoints, and data access.

• Collaborate with development and AI teams to streamline deployment and release processes.

Mandatory Skills

• 2+ years of hands-on experience in Database Administration and DevOps.

• Strong knowledge of MySQL, PostgreSQL, Microsoft SQL Server, and MongoDB.

• Experience with database backup, restoration, replication, indexing, query optimization, and performance monitoring.

• Hands-on experience with Git and CI/CD tools such as Jenkins, GitLab CI/CD, or Azure DevOps.

• Experience with Docker and Kubernetes.

• Experience with AWS, Azure, or GCP.

• Knowledge of Terraform and Ansible.

• Strong Linux administration and shell-scripting skills.

• Experience with Prometheus, Grafana, ELK Stack, or Nagios.

• Working knowledge of networking, security, SSL/TLS, and load balancing.

• Understanding of LLMs, RAG, embeddings, vector databases, and agentic AI architecture.

• Experience deploying Python-based AI/ML services and APIs.

• Familiarity with model-serving tools such as llama.cpp, vLLM, Ollama, Hugging Face, or equivalent.

• Knowledge of GPU-enabled environments, NVIDIA drivers, CUDA, and containerized AI deployment.

• Understanding of AI/LLM observability, model versioning, security, scaling, and rollback.

• Strong troubleshooting, analytical, and problem-solving skills.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline.

• Cloud, DevOps, Linux, database, or Kubernetes certifications are an advantage.

Technical Stack

• Databases: MySQL, PostgreSQL, Microsoft SQL Server, MongoDB and vector databases

• Cloud: AWS, Azure, GCP.

• CI/CD: Jenkins, GitLab CI/CD, Azure DevOps

• Containers and IaC: Docker, Kubernetes, Terraform, Ansible

• Monitoring: Prometheus, Grafana, ELK Stack, Nagios

• AI Infrastructure: Python APIs, LLM serving, RAG, embeddings, vector search, GPU/CUDA

• Operating Systems: Linux—Ubuntu, CentOS, Red Hat

Soft Skills

• Excellent communication and collaboration skills.

• Strong ownership and accountability.

• Ability to work effectively in a fast-paced Agile environment.

• Proactive approach to troubleshooting and continuous improvement.

• Ability to manage multiple priorities and deliver on time.

Review Criteria:

• Strong Dremio / Lakehouse Data Architect profile
• 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
• Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
• Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
• Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
• Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
• Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
• Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
• Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies

Preferred:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments

Role & Responsibilities:

You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

Ideal Candidate:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

Preferred:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.

Job Title : Lead Database Engineer

Location : Gurgaon Sector-43

Experience Required : 4+ Years

Employment Type : Full-Time

Summary :

We are seeking a highly skilled Lead Database Engineer with expertise in managing and optimizing database systems, primarily focusing on Amazon Aurora PostgreSQL, MySQL, and NoSQL databases. The ideal candidate will have in-depth knowledge of AWS services, database architecture, performance tuning, and security practices.

Key Responsibilities :

1. Database Administration :

• Manage and administer Amazon Aurora PostgreSQL, MySQL, and NoSQL database systems to ensure high availability, performance, and security.
• Implement robust backup and recovery procedures to maintain data integrity.

2. Optimization and Performance:

• Develop and execute optimization strategies at the database, query, collection, and table levels.
• Proactively monitor performance and fine-tune RDS parameter groups for optimal database operations.
• Conduct root cause analysis and resolve complex database performance issues.

3. AWS Services and Architecture :

• Leverage AWS services such as RDS, Aurora, and DMS to ensure seamless database operations.
• Perform database version upgrades for PostgreSQL and MySQL, integrating new features and performance enhancements.

4. Replication and Scalability:

• Implement and manage various replication strategies, including master-master and master-slave replication, ensuring data consistency and scalability.

5. Security and Access Control:

• Manage user permissions and roles, maintaining strict security protocols and access controls.

6. Collaboration:

• Work closely with development teams to optimize database design and queries, aligning database performance with application requirements.

Required Skills :

• Strong Expertise: Amazon Aurora PostgreSQL, MySQL, and NoSQL databases.
• AWS Services: Experience with RDS, Aurora, and DMS.
• Optimization: Hands-on experience in query optimization, database tuning, and performance monitoring.
• Replication Strategies: Knowledge of master-master and master-slave replication setups.
• Problem Solving: Proven ability to troubleshoot and resolve complex database issues, including root cause analysis.
• Security: Strong understanding of data security and access control practices.
• Collaboration: Ability to work with cross-functional teams and provide database-related guidance.

Preferred Qualifications :

• Certification in AWS or database management tools.
• Experience with other NoSQL databases like MongoDB or Cassandra.
• Familiarity with Agile and DevOps methodologies.

Oracle OAS Developer

Senior OAS/OAC (Oracle analytics) designer and developer having 3+ years of experience. Worked on new Oracle Analytics platform. Used latest features, custom plug ins and design new one using Java. Has good understanding about the various graphs data points and usage for appropriate financial data display. Worked on performance tuning and build complex data security requirements.

Qualifications

Bachelor university degree in Engineering/Computer Science.

Additional information

Have knowledge of Financial and HR dashboard

Rajasthan Studio is looking for young and bright minds for its upcoming innovative, never-experienced-before app platform for virtual art experiences.

We are looking for programmers with problem-solving skills and critical thinking abilities for the position of Back End developer. Back End developers are responsible for creating a bridge between customers and business logic, optimizing applications for maximum efficiency, creating dashboards for internal teams, and maintaining brand consistency across the application, among other duties.

Backend Web Developers are responsible for managing the interchange of data between the server and the users. The role's primary focus will be the development of all server-side logic, definition, and maintenance of the central database, and ensuring high performance and responsiveness to requests from the front-end. A basic understanding of front-end technologies is necessary as well.

Responsibilities -

• Creating RESTful API/GraphQL to be consumed by Flutter developers
• Building reusable code and libraries for future use
• Optimization of the application for maximum speed and scalability
• Implementation of security and data protection
• Design and implementation of data storage solutions
• Participate in the entire application lifecycle, focusing on coding and debugging
• Write clean code to develop functional web applications
• Troubleshoot and debug applications
• Provide training and support to internal teams

Skill & Qualifications -

• Basic understanding of front-end technologies and platforms, such as JavaScript, HTML5, and CSS3
• Understanding accessibility and security compliances
• User authentication and authorization between multiple systems, servers, and environments
• Integration of multiple data sources and databases into one system
• Management of hosting environment, including database administration and scaling an application to support load changes
• Data migration, transformation, and scripting
• Setup and administration of backups
• Outputting data in different formats
• Understanding differences between multiple delivery platforms such as mobile vs desktop, and optimizing output to match the specific platform
• Creating database schemas that represent and support business processes
• Implementing automated testing platforms and unit tests
• Proficient understanding of code versioning tools, such as Git
• Proficient understanding of OWASP security principles
• Understanding of “session management” in a distributed server environment
• Knowledge of Yii framework - version 2 (preferred)

Essential duties and responsibilities include the following.

• Design, create and maintain databases through multiple product lifecycle environments, from development to production systems
• Configure and maintain database servers and processes, monitor system health and performance, to ensure high levels of performance, availability, and security.
• Convert complex business requirements into technical specifcations to build scalable and reliable data solutions 
• Apply data modelling techniques to ensure development and implementation support efforts meet integration and performance expectations.
• Independently analyse, solve, and correct issues in real time on production, providing problem resolution end-to-end.
• Refine and automate regular processes, track issues, and document changes.
• Develop complex query, performance tuning, stored procedures and triggers, scheduled jobs, schema refinement.
• Flexibility to work after office hours for any production issue or production deployment.
• Perform scheduled maintenance and support release deployment activities after hours.
• Share domain and technical expertise, providing technical mentorship and cross-training to other peers and team members.

Qualifications include:

• 4+ years of database and backend development experience
• Good understanding of database systems and architectures
• Expertise in writing complex SQL queries and stored procedures
• Hands on experience with RDBMS and NoSQL data stores like  MySQL and MongoDB
• Experience working with Python scripting and application development
• Experience working with Cloud applications and data stores like AWS RDS is a plus
• In-depth understanding of data management and ETL processes