Line of Service

AdvisoryIndustry/Sector

Not ApplicableSpecialism

Data, Analytics & AIManagement Level

Senior Associate & Summary

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life.

Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

& 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 recent 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

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Master of Business Administration, Bachelor of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)

Required Skills

QA AutomationOptional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline {+ 38 more}Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not SpecifiedAvailable for Work Visa Sponsorship?

NoGovernment Clearance Required?

NoJob Posting End Date

May 19, 2026

📌 IN_Senior Associate_AI Engineer _Data& Analytics_Advisory_Bangalore (Bengaluru)
🏢 PwC
📍 Bengaluru