Director - AI Architect, Data and Analytics

PriceWaterhouseCoopers Pvt Ltd ( PWC ); Bengaluru; On-site; INR 4,000,000 - 9,000,000; Full time

Job summary

PriceWaterhouseCoopers Pvt Ltd (PwC) in Bengaluru seeks an experienced AI Architect for Data and Analytics Advisory. You will design ML pipelines, build scalable APIs, and lead LLM serving with GPU-accelerated architectures for client engagements.

You will collaborate with cross-functional teams to deploy state-of-the-art AI solutions, leadDevOps/LLMOps efforts, and mentor junior engineers while delivering strategic insights. PwC emphasizes inclusion, growth, and impact.

Qualifications

• Experience in designing ML pipelines for experiment management and model retraining.
• APIs for scalable model inference at production scale.
• Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI.
• Deep knowledge of GPU architectures and distributed training for large language models.
• DevOps and LLMOps practices with Kubernetes, Docker; familiarity with Flowise and Langflow.

Responsibilities

• Lead ML pipeline design and model retraining workflows for client projects.
• Architect LLM serving and GPU infrastructure to improve latency and throughput.
• Guide model fine-tuning and optimization to balance accuracy and compute.
• Implement DevOps/LLMOps practices; manage container orchestration and deployment pipelines.
• Collaborate with data engineering and client teams to deliver scalable AI solutions.

Skills

Python

SQL

JavaScript

LLM Ops

Kubernetes

Docker

Deep Learning

ML Pipeline Design

Education

B.Tech/MCA/BCA/M.tech

Tools

MLflow

SageMaker

Vertex AI

Azure AI

Job description

IN_Director_AI Architect_Data and Analytics_Advisory_Bangalore Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Director Job Description & 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 business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decision-making for clients. You will develop and implement innovative solutions to optimise business performance and enhance competitive advantage. *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.

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, Javascript

Mandatory skill sets

• 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, Javascript

Preferred skill sets

• 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, Javascript

Years of experience required

8-16 years

Education qualification

B.Tech/MCA/BCA/M.tech

Degrees/Field of Study required

Bachelor of Engineering, Master of Business Administration, Bachelor of TechnologyDegrees/Field of Study preferred

Required Skills

AI Architecture Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Applied Macroeconomics, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Coaching and Feedback, Communication, Competitive Advantage, Continuous Process Improvement, Creativity, Data Analysis and Interpretation, Data Architecture Development, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Embracing Change, Emotional Regulation, Empathy {+ 36 more}

Desired Languages

(If blank, desired languages not specified)

Travel Requirements

Up to 60%

Available for Work Visa Sponsorship

No

Government Clearance Required

No

Job Posting End Date

September 9, 2026

Experience Level

Senior Level