While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role: Lead/Associate Lead – QA + MLOps & Generative AI Experience: 10+ years Location: Mumbai/Bangalore (Hybrid) Key Responsibilities AI/ML & GenAI Testing Strategy (AWS Ecosystem) Define testing approaches for AI systems built on AWS services such as:
- Design reusable AI testing accelerators
- Create AWS-aligned AI test automation frameworks (Python-first)
- Develop synthetic data generation strategies
- Establish AI quality scorecards
- Build an internal AI QA Center of Excellence
Client Engagement & Leadership
- Lead AI/ML quality strategy workshops
- Perform AI risk & readiness assessments
- Present quality architecture to CXOs
- Drive QA transformation programs
- Mentor QA teams on AWS-based AI testing
- Own delivery for AI testing engagements end-to-end
Must Have Skills Testing Expertise
- 8–12+ years in Quality Engineering
- Strong test strategy, automation & governance experience
- Experience leading QA transformation initiatives
- Experience building frameworks from scratch AI/ML & GenAI Expertise
- Deep understanding of ML lifecycle
- Experience testing ML models (NLP preferred)
- Hands-on experience validating LLM applications
- Solid understanding of:
- Prompt engineering
- RAG architecture
- Embeddings
- Bias & explainability AWS AI/ML Expertise
- Hands-on experience with:
- Amazon SageMaker (training, deployment, monitoring)
- Amazon Bedrock (LLM integration & evaluation)
- S3-based data pipelines
- AWS IAM (security validation)
- CloudWatch monitoring
- Lambda & API Gateway integrations
- AWS CI/CD (CodePipeline / CodeBuild preferred)
Understanding Of
- Infrastructure as Code (Terraform / CloudFormation)
- Observability in AI systems
- Cost monitoring for ML workloads
Technical Skills
- Python (mandatory)
- Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch)
- Experience with LLM frameworks (LangChain, etc.)
- API & automation testing frameworks
- Git-based workflows
- Leadership & Communication
- Strong client-facing communication
- Experience leading QA teams
- Ability to create strategy decks & solution proposals
- Strong stakeholder management
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !