IN_Senior Associate_AI Engineer _Data& Analytics_Advisory_Bangalore

Job Description & Summary: QA Automation Lead

Responsibilities: ML Pipeline Design: Design ML pipelines for experiment management, model management, feature management, and model retraining. Design APIs for model inferencing at scale. Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. LLM Serving and GPU Architecture: Possess deep knowledge of GPU architectures. Expertise in distributed training and serving of large language models. Proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM. Model Fine-Tuning and Optimization: Demonstrate proven expertise in model fine-tuning and optimization techniques. Achieve better latencies and accuracies in model results. Reduce training and resource requirements for fine-tuning LLM and LVM models. DevOps and LLMOps Proficiency: Proven expertise in DevOps and LLMOps practices. Knowledgeable in Kubernetes, Docker, and container orchestration. Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph. Skill Matrix LLM: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery. Cloud Knowledge: AWS/Azure/GCP Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert Proficient in Python, SQL, Javascrip

Automation Leadership

• Lead all automation initiatives for the Analytics team.

• Drive key automation KPIs:

• 100% automation coverage

• 100% execution rate with 100% pass rate

• Reduce execution time to ≤3 hours

• Achieve 80% code coverage via automation tests

• Guide, mentor, and review test automation engineers to ensure adherence to best practices and coding standards.

Implement AI agents for:

• Self-healing locators

• Autonomous test execution

• Intelligent retry and Recovery

• Support multi-turn test scenarios and dynamic test flows

• Experience using or integrating AI agents / self-healing mechanisms

• Exposure to AI-driven testing tools

Framework & Tooling Development

• Design and build scalable, extensible test automation frameworks.

• Support parameterized test case creation and multi‑environment test execution.

• Research, evaluate, and recommend new tools and technologies to address testing challenges.

• Develop and maintain scripts to support testing tasks.

Execution & Reporting

• Plan, coordinate, and manage all automated testing activities.

• Develop, execute, and maintain test plans, scripts, and test cases.

• Analyze test results, identify defects, and recommend corrective actions.

• Maintain documentation of test execution and results.

• Provide regular test status updates and manage stakeholder expectations.

• Create and maintain traceability matrices to ensure comprehensive requirement coverage.

Quality and Performance

• Drive automated regression, performance, load, and scalability testing.

• Ensure product quality across frontend, backend, data pipelines, and integrations.

• Collaborate closely with development teams in Agile/Scrum environments.

Required Technical Skills

• 8+ years of QA experience testing Java/J2EE and web‑based applications.

• Strong automation background with Selenium, TestNG, JUnit, and other open‑source tools.

• Experience testing data pipelines using pytest or equivalent frameworks.

• Understanding of PySpark and Databricks(optional).

• Strong programming experience in Java or another OOP language.

• Experience with performance testing (optional).

• Proficiency with QA tools such as JIRA, test management systems, CI/CD systems.

• Good understanding of HTTP, SSL, HTML, XML, CSS, JavaScript, SQL, and debugging techniques.

• Experience in Agile/Scrum development environments.

Other Required Skills

• Bachelor’s or Master’s degree in Computer Science or equivalent.

• Strong problem‑solving, analytical, and debugging skills.

• Ability to understand new technologies quickly.

• High attention to detail, reliability, and ownership mindset.

• Ability to work independently and collaboratively across teams.

• Strong communication skills—written and verbal.

• Excellent organizational and time‑management abilities.

• Ability to work in environments with limited standardization and evolving requirements.

Mandatory skill sets: • Gen AI,LLM, Huggingface, python,pytorch/tensor flow/keras, Langchain, Langgraph, Docker, Kunernetes

Preferred skill sets (Good to Have):

• QA Automation Lead

Years of experience required:

5-8 years

Education qualification:

BE/B.Tech/MBA/MCA