QA platform engineer Devops(Bangalore only)

PwC; Bengaluru; On-site; INR 3,000,000 - 4,200,000; Full time

Job summary

PwC Bengaluru seeks a senior QA engineer focusing on automation and AI-driven testing frameworks. You will build and validate AI-based testing strategies across cloud environments, embedding LLMs into CI/CD pipelines, and work with platform/SRE teams to improve reliability.

The ideal candidate has 6+ years in QA automation or software engineering, 3+ years in AI-driven testing, and hands-on experience with Azure DevOps, GitHub Actions, and cloud AI services on Azure or AWS.

Qualifications

• 6+ years of experience in QA automation or software engineering.
• 3+ years of experience working with AI-driven automation or intelligent testing frameworks.
• Minimum 2 years of hands-on experience in building or testing AI-based tools or platforms.

Responsibilities

• Build and operate CI/CD integrated test execution for AI/ML/GenAI workflows across environments.
• Validate system, integration, and end-to-end workflows for AI platforms (agents, APIs, RAG services, model endpoints, pipelines).
• Establish test reporting and observability (quality gates, run analytics, pipeline health, deployment risk visibility).
• Implement cloud-based AI testing strategies on Azure/AWS, including environment readiness and service integration checks.

Skills

QA automation

AI-driven automation

hands-on AI tools testing

Education

Bachelor's or Master's in CS/Engineering/Data Science

Tools

Azure DevOps

GitHub Actions

Cloud AI services (Azure/AWS)

CI/CD test orchestration

API & integration testing tools

Observability dashboards

AWS CloudWatch / Grafana / Prometheus

Job description

Key Responsibilities:

• 6+ years of experience in QA automation or software engineering.
• 3+ years of experience working with AIdriven automation or intelligent testing frameworks.
• Minimum 2 years of handson experience in building or testing AIbased tools or platforms.

Tools & Technologies

Build and operate CI/CDintegrated test execution for AI/ML/GenAI workflows across environments

• Validate system, integration, and endtoend workflows for AI platforms (agents, APIs, RAG services, model endpoints, pipelines)
• Establish test reporting and observability (quality gates, run analytics, pipeline health, deployment risk visibility)
• Implement cloud-based AI testing strategies on Azure/AWS, including environment readiness and service integration checks

• Automate deployment validation including contract testing, dependency checks, and rollback verification
• Embed LLMs into CI/CD pipelines for:
• Intelligent test orchestration (prioritization, dynamic suite selection)
• Guardrails enforcement (policy checks, response constraints, safety rules)
• Automated compliance & security checks in AI deployments
• Partner with platform/SRE/engineering teams to improve reliability using SRE principles (SLIs/SLOs, error budgets, incident learnings)
• Support security & compliance awareness through scanning, policy enforcement, secrets management, and auditready reporting
• Qualifications and Skills:
• Bachelors or masters degree in computer science, Engineering, Data Science, or equivalent experience.
• Must Have Tools
• Azure DevOps / GitHub Actions
• Cloud AI services (Azure/AWS)
• CI/CD test orchestration
• API & integration testing tools
• Observability dashboards
• AWS CloudWatch / Grafana / Promethe