IN_Senior Associate_Generative AI Engineer _Emerging Business

PwC Service Delivery Center; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

PwC Service Delivery Center in Bengaluru seeks a GenAI Engineer to design, develop, and deploy scalable GenAI solutions using LLMs and transformer architectures. You will work with Python, PyTorch, and Hugging Face Transformers, deploying models on Azure, AWS, or GCP, and building robust APIs.

You'll orchestrate model workflows, experiment with prompts and fine‑tuning, and implement ML pipelines with LangChain, FastAPI, MLflow, and Weights & Biases, while promoting ML CI/CD best practices.

Qualifications

• Extensive experience designing GenAI solutions using LLMs and transformer architectures.
• Hands-on deployment of GenAI models on major cloud platforms with scalable pipelines.

Responsibilities

• Design, build, and deploy generative AI solutions using LLMs such as OpenAI or open‑source models.
• Fine‑tune and customize foundation models using domain‑specific datasets.
• Develop and optimize prompt engineering strategies for accurate outputs.
• Implement model pipelines using Python and ML frameworks like PyTorch, Hugging Face, or LangChain.

Skills

GenAI proficiency

LLMs

Prompt engineering

Python

PyTorch

Hugging Face Transformers

LangChain

API development (FastAPI/Flask)

MLOps practices

Tools

Azure

AWS

GCP

Azure ML

SageMaker Pipelines

MLflow

Weights & Biases

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.

This role demands deep expertise in Python, PyTorch, and Hugging Face Transformers, along with hands‑on experience in deploying solutions on Azure, AWS, or GCP. The candidate should be proficient in using orchestration frameworks like LangChain, developing APIs with FastAPI or Flask, and managing ML pipelines using tools such as MLflow or Weights & Biases. Familiarity with CI/CD practices for ML, including platforms like Azure ML or SageMaker Pipelines, is essential.

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 Crew.ai or LangChain.
• Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP).
• Knowledge on Azure/GCP/AWS AI platforms 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.
• Keep up to date with the latest research in GenAI, foundation models, and relevant open‑source tools.

Skills

• Generative AI
• LLMs
• Prompt engineering
• PyTorch
• Hugging Face Transformers
• LangChain
• FastAPI
• MLOps
• Cloud platforms (Azure/AWS/GCP)

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.