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Über diese GenAI Engineer - Senior Associate Stelle bei PwC

PwC · Vor Ort · Mexico - Reforma 445

Industry/Sector

Not Applicable

Specialism

Managed Services

Management Level

Senior Associate

Job Description & Summary

The Opportunity

Join our Acceleration Center Mexico and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a GenAI Engineer - Senior Associate you will apply data, algorithms, and software engineering to build and deploy AI and machine learning solutions at scale within our Data and Analytics Engineering practice. As a Senior Associate you will analyze complex problems, manage assigned workstreams, mentor junior team members, and build meaningful client connections while navigating ambiguity and maintaining professional and technical standards. This role offers the chance to shape AI systems, data pipelines, and software components that turn raw information into usable insights for client needs.

In this role at PwC, you will contribute to a fast-moving environment where you adapt to a variety of client challenges, take ownership of your deliverables, and support the delivery of dependable AI solutions. You will work across design, data wrangling, implementation, and ongoing platform support, with a focus on interpreting feedback, applying critical thinking, and developing a deeper understanding of the business context.

Responsibilities

- Designing and developing AI and machine learning solutions that transform raw data into usable insights
- Building data pipelines, data models, and data integration workflows to support scalable AI systems
- Applying Python, machine learning libraries, and software engineering methods to develop and maintain GenAI capabilities
- Tuning model performance and supporting deployment activities across AI platforms and managed service environments
- Analyzing complex data sources to identify patterns, improve model outputs, and inform technical recommendations
- Supporting data quality, observability, and platform maintenance across client data and analytics environments
- Translating business needs into technical requirements for text analytics, natural language processing, and related AI use cases
- Reviewing assigned workstreams and contributing to deliverables while guiding junior team members as needed

What You Must Have

- At least a Bachelor's degree
- At least 3 - 5 years of experience
- Oral and written proficiency in English required

What Sets You Apart

- Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- 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
- Demonstrating hands-on GenAI development using Python, data pipelines, or cloud services
- Applying machine learning, natural language processing, or text analytics in client delivery work
- Translating business needs into AI solutions through clear stakeholder communication
- Navigating ambiguity while managing multiple workstreams in managed services environments

Travel Requirements

Up to 20%

Job Posting End Date

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Über PwC

Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.

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