Line of Service
Advisory

Industry/Sector
Not Applicable

Specialism
Data, Analytics & AI

Management Level
Associate

Job Description & Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

*Why PWCAt 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 Crew.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.
Keep up to date with the latest research in GenAI, foundation models, and relevant open-source tools.

Mandatory skill sets:

Generative AI (LLMs, Transformers)
Python, PyTorch, Hugging Face Transformers
Azure/AWS/GCP cloud platforms
LangChain/Langgraph or similar orchestration frameworks
REST APIs, FastAPI, Flask
ML pipeline tools (MLflow, Weights & Biases)
Git, CI/CD for ML (e.g., Azure ML, SageMaker pipelines)

Preferred skill sets:

RAG (Retrieval-Augmented Generation)
Vector DBs (FAISS, Pinecone, Weaviate)
Streamlit/Gradio for prototyping
Docker, Kubernetes (for model deployment)
Data preprocessing & feature engineering
NLP libraries: spaCy, NLTK, Transformers

Years of experience required:

3 to 5 years

Education qualification:

B.E/B.tech/M.tech/MCA

Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Engineering, Bachelor of Engineering, MBA (Master of Business Administration)

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills
Generative AI

Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Strategy + 22 more

Desired Languages (If blank, desired languages not specified)

Travel Requirements
Not Specified

Available for Work Visa Sponsorship
No

Government Clearance Required
No

Job Posting End Date
April 21, 2026

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