AI Engineer

Responsibilities

• Designing and implementing AI systems to transform raw data into actionable insights
• Developing scalable machine learning models using Python and TensorFlow
• Integrating data from various sources to create unified views for analysis
• Building and maintaining data pipelines to support AI model deployment
• Applying complex data analysis techniques to discern patterns and trends
• Collaborating with team members to enhance AI solutions and drive business growth
• Utilizing natural language processing tools like NLTK for text analytics and sentiment analysis
• Implementing neural networks and deep learning methods for advanced AI applications
• Managing data quality and infrastructure to support reliable AI operations
• Engaging in continuous learning to adapt to new technologies and methodologies in AI engineering

Requirements

• At least a Bachelor's degree or, in lieu of a degree, at least 1 years of experience in Engineering with AI and Machine Learning
• At least 1 years of experience

Qualifications

• In at least one of the following fields of study: Computer and Information Science, Computer Engineering, Computer Management, Management Information Systems, Information Technology
• In at least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
• Building and orchestrating AI agent workflows using frameworks such as LangGraph to automate multi-step reasoning, integrate tools and APIs, and deliver scalable, context-aware solutions
• Applying generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models
• Developing automated evaluation frameworks, including LLM-as-judge pipelines, regression testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output groundedness
• Optimizing open-weight language models, including LLaMA, Mistral, and Gemma, for local and cloud deployment using quantization, inference acceleration, and model-routing techniques
• Designing agent harnesses and implementing context engineering, memory management, retry logic, and structured output validation to support reliable, multi-step AI workflows
• Utilizing machine learning libraries like Scikit-Learn for data analysis
• Implementing AI solutions using open-source software
• Applying natural language processing techniques in real-world applications

Pay

The salary range for this position is: $50,500 - $112,500. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws.

Benefits

PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

About the Role

This role is within the Internal Firm Services practice and involves applying data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based solutions at scale.