Associate Lead - Testing (QA + MLOps)
Quantiphi
Associate Lead - Testing (QA + MLOps) at Quantiphi is a full time role based in IN KA Bengaluru, India. It was published on 24 March 2026 and was open at last check.
| Role | Associate Lead - Testing (QA + MLOps) |
|---|---|
| Company | Quantiphi |
| Location | IN KA Bengaluru, India |
| Employment type | Full Time |
| Published | 24 March 2026 |
| Status | Open at last check |
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:
- Amazon SageMaker
- Amazon Bedrock
- AWS Lambda
- Amazon API Gateway
- Amazon Kinesis
- AWS Glue
- Amazon S3
- Amazon CloudWatch
Design validation frameworks covering:
- Model accuracy & performance validation
- Data drift & concept drift detection
- Hallucination detection for LLMs
- Prompt robustness testing
- RAG validation (retrieval accuracy + grounding)
- Bias & fairness validation
- Safety & toxicity testing
MLOps Quality Engineering (AWS-Centric)
Validate the end-to-end ML lifecycle including:
- Data ingestion & feature pipelines
- Model training & hyperparameter tuning
- Model versioning & registry
- Deployment validation
- Canary & blue/green release validation
Work with AWS-native services such as:
- SageMaker Pipelines
- SageMaker Model Monitor
- SageMaker Feature Store
- Bedrock model evaluation workflows
- CloudWatch-based observability
Implement CI/CD quality gates for ML pipelines integrated with AWS DevOps tools.
GenAI & Agentic AI Testing
Define quality engineering approaches for:
- LLM-based applications using Amazon Bedrock
- Prompt engineering validation
- Multi-agent orchestration testing
- Chatbot & Voice bot conversational testing
- Intent classification validation
- Conversation drift & fallback validation
- API contract validation for LLM integrations
Build reusable evaluation harnesses for:
- BLEU / ROUGE scoring
- Embedding similarity scoring
- Response consistency
- Safety scoring frameworks
Framework & Capability Development
- 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
- Strong 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!
Create your free OnJob profile to apply — we'll take you to Quantiphi's application after sign-up. · Posted 24 Mar 2026.
Associate Lead - Testing (QA + MLOps) at Quantiphi — questions answered
What does the Associate Lead - Testing (QA + MLOps) role at Quantiphi pay?
Quantiphi does not publish a salary on this Associate Lead - Testing (QA + MLOps) listing, so OnJob shows no figure for it rather than an estimate. For what this role pays across the market, the OnJob salary guides aggregate the live listings that do disclose pay.
Where is the Associate Lead - Testing (QA + MLOps) role at Quantiphi based?
Quantiphi lists this Associate Lead - Testing (QA + MLOps) role in IN KA Bengaluru, India, advertised as full time work at that location. Larger employers sometimes cover several sites under one city name, so confirm the exact office with Quantiphi before you apply.
Is the Associate Lead - Testing (QA + MLOps) role at Quantiphi still open?
The Associate Lead - Testing (QA + MLOps) posting at Quantiphi was open at OnJob's last check of the employer's careers page, having been published on 24 March 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
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