IN_Senior Associate_AI Engineer_GCC_Advisory_Chennai

PwC; Chennai; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

PwC India in Chennai seeks an AI Engineer to design ML pipelines, manage model inference APIs, and implement MLOps practices. You will work with GPUs, distributed training, and LLMs to deliver scalable analytics solutions.

The role requires 5–8 years of experience, a strong background in Python and data analytics, and hands-on expertise with frameworks like HuggingFace and Langchain. Join a dynamic advisory team at PwC.

Qualifications

• Experience with AI/ML systems and data analytics.
• Ability to design and deploy ML pipelines and APIs for model inference.
• Strong knowledge of large language models, model serving, and distributed training.
• Experience with DevOps practices for ML (LLMOps) and container orchestration.

Responsibilities

• Design ML pipelines for experiment management and model retraining.
• Develop APIs for scalable model inferencing.
• Manage GPU architectures and distributed training for LLMs.
• Implement LLM orchestration frameworks and DevOps practices.

Skills

Gen AI

LLM

Analytical Thinking

Data Analysis

Project Management

Education

Bachelor of Technology

MCA/M.tech

Tools

MLflow

SageMaker

Vertex AI

Azure AI

Kubernetes

Docker

Langchain

Langgraph

Langflow

Flowise

HuggingFace

Job description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate

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.

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.

AI Engineer

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
• Programming Languages & Frameworks: Python, SQL, Javascript
• Mandatory skill sets: Gen AI, LLM, Huggingface, python, pytorch/tensor flow/keras, Langchain, Langgraph, Docker, Kubernetes
• Years of experience required: 5-8 years
• Education qualification: B.Tech/MCA/BCA/M.tech
• Degrees/Field of Study required: Bachelor of Technology
• 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, 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

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