Senior Associate - Project Management in Data and Analytics

PriceWaterhouseCoopers Pvt Ltd ( PWC ); Chennai; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

PwC Chennai seeks a Manager-level AI Engineer in the GCC Advisory practice. The role focuses on building ML pipelines, model management and deploying large language models at scale.

You will work with advanced analytics, GPU architectures, and DevOps practices; experience with MLflow, SageMaker, Vertex AI, Kubernetes, and Docker is preferred. 5–10 years of AI/ML experience is expected.

Qualifications

• Gen AI, LLM, Huggingface, Python, PyTorch, TensorFlow, Keras.
• LangChain, Langgraph, Docker, Kubernetes.
• Experience in ML pipelines, model management and inference APIs.

Responsibilities

• ML Pipeline Design for experiment and model management; design APIs for model inference at scale.
• LLM Serving and GPU architecture with distributed training and serving of large language models.
• Model fine-tuning and optimization to improve latency and accuracy; reduce training/resource needs.
• DevOps and LLMOps practices; Kubernetes and Docker; Flowise, Langflow, Langgraph integrations.

Skills

Gen AI

LLM

HuggingFace

Python

PyTorch

TensorFlow

Keras

LangChain

Langgraph

Docker

Kubernetes

LLM Ops

Education

B.Tech

MCA

BCA

M.Tech

Tools

SageMaker

Vertex AI

Azure AI

ML Flow

Langraph

LangFlow

Job description

Open Position

IN_Manager_AI Engineer_GCC_Advisory_Chennai

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

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 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.

Equal Employment Opportunities

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 such as 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

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

Preferred Skill Sets

• 5-8 years

Experience and Education

• Years of Experience required: 5 to 10
• Education qualification: B.Tech/MCA/BCA/M.tech
• Degrees/Field of Study required: Bachelor of Technology
• Degrees/Field of Study preferred:
• Certifications (if blank, certifications not specified)
• Required Skills Project Management Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Fluency, AI-Human Collaboration, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Coaching and Feedback, 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 {+ 46 more}

Job Details

• Travel Requirements Not Specified
• Available for Work Visa Sponsorship? No
• Government Clearance Required? No
• Job Posting End Date September 20, 2026
• Experience Level Senior Level