Senior AI Engineer

Job Description & Summary

Join Us to Shape the Future with AI and Innovation

At Commercial Technology & Innovation (CT&I), we’re not just building technology—we’re reshaping the future of business. As the tech engine behind PwC’s Advisory platforms, we embed AI, automation, and cutting-edge engineering into everything we do, delivering smarter, faster, and bolder solutions that drive real-world impact. Our mission is to power possibility—partnering with bold thinkers to turn vision into reality and transform industries at scale.

We’re looking for passionate, curious, and purpose-driven engineers who want to make a difference. If you’re ready to innovate with intent, drive business outcomes, and help lead the AI-enabled transformation of one of the world’s most trusted organizations, your journey starts here.

The Opportunity

We’re seeking an innovative and versatile AI Engineer who combines strong machine learning expertise with modern application development skills. In this role, you’ll design and deploy AI-powered solutions that are scalable, user-friendly, and integrated within real-world applications. You’ll work cross-functionally with data scientists, ML engineers, backend / frontend developers, and product teams to deliver impactful AI products.

Job Requirements and Preferences :

Basic Qualifications :

Minimum Degree Required : Bachelor Degree

Minimum Years of Experience : 3 years

Preferred Qualifications :

Degree Preferred : Master Degree

Preferred Fields of Study : Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field

Preferred Knowledge / Skills :

• Designing, training, and deploying machine learning models and Large Language Models (LLMs) into production environments.
• Developing scalable, cloud-native microservices using tools like Docker and Kubernetes.
• Building end-to-end AI applications integrated into web, mobile, or API-first platforms.
• Managing CI / CD pipelines and observability for AI systems using tools such as GitHub Actions and MLflow.
• Implementing vector databases, Retrieval-Augmented Generation (RAG) pipelines, and orchestration tools like LangChain and LlamaIndex.
• Building and integrating multi-agent frameworks (e.g., LangGraph, LangFlow) to enable autonomous AI task execution.
• Translating complex business problems into software-engineered AI solutions aligned with best practices.
• Deploying on cloud platforms (AWS, GCP, Azure) and leveraging services such as SageMaker, Vertex AI, or Databricks.
• Proficiency in Python and ML frameworks like PyTorch, TensorFlow, and Hugging Face Transformers.
• Collaborating in cross-functional engineering environments including front-end (React, Next.js) and platform teams.
• Familiarity with LLM providers (OpenAI, Anthropic, Meta, etc.) and working with chat / image-based model outputs.
• Hands-on experience with agent-based frameworks for intelligent orchestration.

Additional experience or qualifications considered a plus :