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Principal Software Engineer

  • Source: Workday
  • Cadence
  • On-site
  • Bengaluru
  • Full-Time
  • Staff

Job Description

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Senior AI Test / Automation Engineer

Overview

Role: AI Test / Automation Engineer
Location: Bangalore India

Department: AI Engineering / Quality Assurance
Experience Level: Mid to Senior

We are looking for a highly motivated Senior AI Test / Automation Engineer to design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems. This role is critical to ensure that AI solutions meet enterprise standards for quality, reliability, safety, and compliance before and after production deployment.

Key Responsibilities

  • Build and maintain AI test automation frameworks for pre-qualification and continuous validation of models and agent workflows
  • Develop comprehensive test suites, including:
    • Unit, integration, and end-to-end (E2E)
    • Functional, regression, performance, and safety testing
  • Validate AI system behavior, including:
    • Non-deterministic LLM outputs
    • Hallucinations and edge cases
    • Multi-step agent decision-making
  • Design and manage evaluation systems:
    • Golden datasets
    • Benchmarking pipelines (accuracy, latency, reliability)
  • Automate testing within CI/CD pipelines for model updates, prompt changes, and tool integrations
  • Implement observability and telemetry to enable traceability, monitoring, and audit readiness
  • Collaborate cross-functionally with ML, MLOps, Product, and Security teams to define quality gates and release criteria
  • Track and report quality KPIs, including test coverage, defect leakage, and system reliability
  • Drive root-cause analysis and continuous improvement across the AI testing lifecycle

Required Skills

Core Engineering

  • Strong programming skills in Python; familiarity with Bash, TypeScript, or Go
  • Experience with test automation frameworks such as PyTest, Playwright, Selenium, or Cypress
  • Proficiency in CI/CD tools (GitHub Actions, Jenkins, GitLab CI)
  • Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)

AI / ML & Agentic Systems

  • Hands-on experience with LLM ecosystems (OpenAI, Anthropic, Bedrock)
  • Familiarity with:
    • RAG architectures and vector databases (Pinecone, Weaviate)
    • Agent frameworks (LangChain, LlamaIndex, AutoGen)

AI Testing Techniques

  • Experience with non-deterministic testing approaches (statistical assertions, tolerance thresholds)
  • Knowledge of evaluation methods:
    • LLM-as-a-judge
    • BLEU, ROUGE, semantic similarity scoring
  • Experience with prompt and agent regression testing
  • Understanding of AI safety testing, including adversarial testing, bias/fairness validation, and jailbreak detection

Tooling (Preferred)

  • AI testing & observability tools: LangSmith, TruLens, Arize, Weights & Biases
  • Evaluation tools: DeepEval, Ragas, PromptFoo, Giskard
  • Monitoring: Prometheus, Grafana, OpenTelemetry

Soft Skills

  • Strong analytical and problem-solving skills
  • Excellent communication and cross-functional collaboration
  • Data-driven mindset with focus on quality KPIs
  • Detail-oriented with a strong bias toward automation and scalability

Experience Requirements

  • 7+ years in QA, SDET, or test automation engineering
  • Proven experience building and scaling automation frameworks
  • Hands-on experience with AI/ML systems or LLM-based applications

  • Experience testing RAG pipelines or agentic workflows
  • Owned end-to-end AI test strategy and architecture
  • Defined quality metrics and release gates
  • Delivered scalable validation pipelines for production AI systems
  • Supported audit and compliance readiness

Preferred

  • Experience in enterprise or regulated environments (SOC2, ISO 27001, etc.)
  • Exposure to:
    • Shift-left testing practices
    • Production observability and monitoring
    • Chaos or resilience testing

Senior-Level Differentiators

Education

  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

Nice-to-have:

  • ISTQB certification
  • Cloud/ML certifications (AWS, Azure, GCP)
  • AI testing certifications

What Success Looks Like

  • AI systems that are accurate, reliable, and safe
  • Fully automated test pipelines integrated into CI/C…

Skills

  • Python
  • TypeScript
  • microsoft-typescript
  • Golang
  • Pytest
  • Playwright
  • selenium
  • Cypress
  • Github
  • github-actions
  • Jenkins
  • gitlab
  • gitlab-ci
  • amazon-web-services
  • microsoft-azure
  • google-cloud-platform
  • Docker
  • Kubernetes
  • openai
  • bedrock
  • LangChain
  • LlamaIndex
  • bleu
  • Prometheus
  • Grafana
  • opentelemetry
  • workday

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