IN_Sr Associate__Generative AI Engineer_Advisory_Bangalore
PricewaterhouseCoopers
- Location
- Bengaluru Millenia
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 236 approvals (FY2023)
- Posted
- Aug 21, 2026
Skills
About this role
Line of Service Advisory Industry/Sector Not Applicable Specialism Emerging Technologies Management Level Senior Associate Job Description & Summary At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions. In emerging technology at PwC, you will focus on exploring and implementing cutting-edge technologies to drive innovation and transformation for clients. You will work in areas such as artificial intelligence, blockchain, and the internet of things (IoT). 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. " Job Description & 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 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