IN_Sr Associate_Generative AI Engineer_Advisory_Bangalore

PwC Service Delivery Center; Bengaluru; On-site; INR 1,800,000 - 2,500,000; Full time

Job summary

PwC Service Delivery Center is seeking a GenAI Engineer to design, develop, and deploy scalable Generative AI solutions using state-of-the-art LLMs and transformer architectures. The role focuses on building intelligent applications, orchestrating model workflows, and integrating GenAI into enterprise systems.

Responsibilities include designing AI solutions with OpenAI, Anthropic, Mistral, and open-source models; fine-tuning models with domain data; optimizing prompts; creating pipelines with

Qualifications

• Experience designing and deploying GenAI solutions with LLMs and transformers.
• Hands-on Python, PyTorch, and ML tooling in cloud environments.
• Ability to productionize GenAI models on Azure, AWS, or GCP.

Responsibilities

• Design, build, and deploy generative AI solutions using LLMs from multiple providers.
• Fine-tune foundation models with domain-specific data.
• Develop and optimize prompt engineering strategies for accuracy.
• Build model pipelines with Python and ML frameworks.
• Collaborate with data engineers and MLOps to productionize models on cloud platforms.
• Implement integration of GenAI into enterprise apps via APIs.
• Evaluate model performance and iterate to improve outputs.

Skills

GenAI engineering

LLMs

Transformer architectures

Prompt engineering

Python

PyTorch

LangChain

APIs

MLOps

CI/CD for ML

Tools

LangChain

Hugging Face Transformers

FastAPI

Flask

MLflow

Weights & Biases

Azure ML

SageMaker Pipelines

GCP Vertex

Job description

Job Summary

We are seeking a highly skilled and innovative GenAI Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and deploying scalable Generative AI solutions using state-of-the-art large language models (LLMs) and transformer architectures. This includes building intelligent applications, orchestrating model workflows, and integrating GenAI capabilities into enterprise systems.

Responsibilities

• Design, build, and deploy generative AI solutions using LLMs such as OpenAI, Anthropic, Mistral, or open-source models (e.g., LLaMA, Falcon).


• Fine-tune and customize foundation models using domain-specific datasets and techniques


• Develop and optimize prompt engineering strategies to drive accurate and context-aware model responses.


• Implement model pipelines using Python and ML frameworks such as PyTorch, Hugging Face Transformers, or LangChain.


• Agentic AI implementation expertise using C rew.ai or Lang chain


• Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP).


• Knowledge on Azure/GCP/AWS AI platform like Azure AI Foundry or GCP Vertex


• Ensure robustness, scalability, and compliance of AI models in deployment environments.


• Good to have experience in finetuning models


• Good to have experience in SLM


• Integrate GenAI into enterprise applications via APIs or custom interfaces.


• Evaluate model performance using quantitative and qualitative metrics, and improve outputs through iterative experimentation.

Requirements

• Deep expertise in Python, PyTorch, and Hugging Face Transformers, with hands-on experience deploying solutions on Azure, AWS, or GCP


• Proficiency in using orchestration frameworks like LangChain


• Developing APIs with FastAPI or Flask


• Managing ML pipelines using MLflow or Weights & Biases


• Familiarity with CI/CD practices for ML, including platforms like Azure ML or SageMaker Pipelines


• Knowledge on Azure/GCP/AWS AI platforms like Azure AI Foundry or GCP Vertex

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