GenAI Architect/Delivery Lead - Senior Manager

PwC Acceleration Center India; Bengaluru; On-site; INR 900,000 - 1,400,000; Full time

Job summary

PwC Acceleration Center India in Bengaluru seeks a senior GenAI Architect to lead data modernization across cloud analytics. You will shape architectures for data pipelines, data lakes and data warehouses, translating client goals into concrete roadmaps.

You’ll coordinate multi‑disciplinary teams, drive AI fluency and practical GenAI adoption, and guide design choices across Databricks, Snowflake, Azure Data Factory, Airflow, AWS and Azure OpenAI.

Qualifications

• Bachelor’s degree or higher in a related field.
• 12+ years of relevant experience.
• Proficient in English (oral and written).
• Strong Python and data processing framework skills.
• Experience with GenAI architecture and AI workflows.
• Azure DevOps and LLMOps familiarity.
• Experience with data lakes, pipelines, and model fine-tuning.

Responsibilities

• Lead GenAI architecture and delivery for data modernization across cloud analytics.
• Design scalable data and AI solutions linking data architecture, integration, transformation, and validation.
• Translate client objectives into roadmaps for data pipelines, data lakes, data warehouses, and model-driven solutions.
• Coordinate technical teams across Agile delivery cycles, prioritizing tasks, resolving blockers, and managing delivery timelines.
• Advise clients on AI fluency, human‑AI collaboration, and practical adoption of GenAI capabilities within data engineering programs.
• Guiding design decisions for Databricks, Snowflake, Azure Data Factory, Apache Airflow, AWS, and Azure‑based environments
• Reviewing data modeling, performance tuning, query optimization, and database security practices to support stable solution delivery
• Evaluating data quality, data governance, anonymization, and transformation controls across complex engineering solutions
• Communicating project status, risks, tradeoffs, and delivery recommendations to stakeholders and executive leaders
• Coaching team members through technical problem solving, change adoption, and delivery execution across multiple workstreams

Skills

GenAI architecture

Python programming

Spark processing

LLM experience

Team leadership

English proficiency

Education

Bachelor's degree

Tools

Azure DevOps

Kubernetes

Docker

Azure OpenAI Service

Langchain

Llama Index

Semantic Kernel

Spark SQL

Job description

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands‑on learning, cutting‑edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

Responsibilities

• Leading GenAI architecture and delivery workstreams for data modernization initiatives across cloud-based analytics environments
• Designing scalable data and AI solutions that connect data architecture, integration, transformation, and validation across enterprise platforms
• Translating client objectives into implementation roadmaps for data pipelines, data lakes, data warehouses, and model‑driven solutions
• Coordinating technical teams across Agile delivery cycles, prioritizing tasks, resolving blockers, and managing delivery timelines
• Advising clients on AI fluency, human‑AI collaboration, and practical adoption of GenAI capabilities within data engineering programs
• Guiding design decisions for Databricks, Snowflake, Azure Data Factory, Apache Airflow, AWS, and Azure‑based environments
• Reviewing data modeling, performance tuning, query optimization, and database security practices to support stable solution delivery
• Evaluating data quality, data governance, anonymization, and transformation controls across complex engineering solutions
• Communicating project status, risks, tradeoffs, and delivery recommendations to stakeholders and executive leaders
• Coaching team members through technical problem solving, change adoption, and delivery execution across multiple workstreams

What You Must Have

• At least a Bachelor's degree
• At least 12+ years of experience
• Oral and written proficiency in English required
• Advanced programming skills in Python and fluency in data processing frameworks like Apache Spark.
• Should have strong knowledge on LLM’s foundational model (openai GPT4o, O1, Claude, Gemini etc), while need to have strong knowledge on opensource Model’s like Llama 3.2, Phi etc.
• Proven track record with event‑driven architectures and real‑time data processing systems.
• Familiarity with Azure DevOps and other LLMOps tools for operationalizing AI workflows.
• Deep experience with Azure OpenAI Service and vector DBs, including API integrations, prompt engineering, and model fine‑tuning. Or equivalent tech in AWS/GCP.
• Knowledge of containerization technologies such as Kubernetes and Docker.
• Comprehensive understanding of data lakes and strategies for data management.
• Expertise in LLM frameworks including Langchain, Llama Index, and Semantic Kernel.
• Proficiency in cloud computing platforms such as Azure or AWS.
• Exceptional leadership, problem‑solving, and analytical abilities.
• Superior communication and collaboration skills, with experience managing high‑performing teams.
• Ability to operate effectively in a dynamic, fast‑paced environment.

What Sets You Apart

• Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
• Demonstrating GenAI architecture delivery across complex client programs
• Leading data modernization initiatives using cloud engineering platforms
• Applying AI fluency to architect scalable data solutions
• Translating technical direction into actionable stakeholder messages
• Navigating ambiguity while coaching diverse delivery teams