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

Benefits

• PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more.
• All hired individuals are eligible for an annual discretionary bonus.

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.

Schedule

Full time

Benefits

• PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more.
• All hired individuals are eligible for an annual discretionary bonus.

Contact Information

• To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
• To learn more about how we work: https://pwc.to/how-we-work
• For information about anticipated application deadlines: https://pwc.to/us-application-deadlines