AI Engineer Manager AC Manila

PwC Acceleration Center Manila; Taguig; On-site; PHP 1,200,000 - 2,400,000; Full time

Job summary

PwC Acceleration Center Manila is seeking an AI Engineer Manager to lead multidisciplinary teams developing data-driven solutions across advisory and business services. You will transform raw data into actionable insights, guide ML-enabled projects, and ensure data quality and scalable architectures.

You will mentor teammates and drive innovative data engineering approaches to meet client needs. The role emphasizes ownership of projects, budgeting, execution, and relentless delivery with a focus

Qualifications

• At least a Bachelor's degree in a relevant field.
• 7 to 11 years of experience in data/AI engineering or related roles.
• Proficiency in English (oral and written).
• Strong full-stack or backend development skills: Python, Angular/React, RESTful APIs, microservices, SQL/NoSQL, testing, architecture.
• Hands-on experience building AI-enabled applications with LLMs, embeddings, and vector databases.

Responsibilities

• Lead data science initiatives to turn raw data into actionable insights.
• Guide development and deployment of AI-powered data solutions.
• Oversee data pipelines and data lake design for large-scale processing.
• Create data visualizations to communicate insights to stakeholders.
• Manage project timelines and budgets for data-driven deliverables.
• Coach team members to advance data science and analytics skills.
• Collaborate with business leaders to identify data-driven growth opportunities.
• Promote adoption of innovative data engineering technologies and methodologies.
• Ensure data quality and compliance within analytics frameworks.

Skills

Python

Angular/React

RESTful APIs

Microservices

SQL/NoSQL

AI/ML

LangChain/LlamaIndex

Cloud platforms

Docker

Kubernetes

CI/CD

Git

Data pipelines

Data quality

Education

Bachelor's degree

Tools

Docker

Kubernetes

Git

Job description

Job Description:

The Opportunity

Join our Acceleration Center Manila 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 an AI Engineer Manager, you will lead multidisciplinary teams in the design, development, and deployment of data‑driven solutions, transforming raw data into actionable insights that drive business growth. Within our Advisory practice you will leverage advanced analytics and statistical techniques to extract insights from large datasets, enabling informed decision‑making and solving complex business problems.

As a Manager you will enhance your leadership style by motivating and developing your team to deliver quality results. You will be responsible for coaching and leveraging team members' unique strengths to meet client expectations. With your growing business knowledge, you will play a crucial role in identifying opportunities that contribute to the success of our firm. You are expected to lead with integrity and authenticity, articulating our purpose and values meaningfully.

In this role at PwC Acceleration Center Manila, you will take ownership of projects, confirming their successful planning, budgeting, execution and completion. You will embrace technology and innovation to enhance your delivery and encourage others to do the same, fostering a culture of continuous improvement and excellence.

Responsibilities

• Leading data science initiatives to transform raw data into actionable insights for informed decision-making
• Guiding teams in the development and deployment of advanced data solutions using machine learning and artificial intelligence
• Utilizing statistical modeling and predictive analytics to address complex business challenges
• Designing and implementing data pipelines and data lakes to support large-scale data processing
• Overseeing the creation of data visualizations to communicate insights effectively to stakeholders
• Managing project timelines and budgets to deliver data-driven solutions on schedule
• Coaching team members to enhance their skills in data science and analytics
• Collaborating with business leaders to identify opportunities for leveraging data to drive growth
• Promoting the adoption of innovative technologies and methodologies in data engineering and analytics
• Confirming data quality and compliance within analytics frameworks to maintain integrity

What You Must Have

• At least a Bachelor's degree
• At least 7 to 11 years of experience
• Oral and written proficiency in English required
• Strong full-stack or backend development skills, including Python, Angular or React, RESTful APIs, microservices, SQL/NoSQL databases, testing, and software architecture.
• Hands‑on experience building AI-integrated applications, using LLMs, RAG, embeddings, vector databases, and frameworks such as LangChain, LlamaIndex, or Autogen.
• Proven cloud and DevOps capability, including Azure, AWS, or GCP deployment, Docker, Kubernetes, CI/CD, Git, security, reliability, and scalability.

What Sets You Apart

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Demonstrating proficiency in data science algorithms and workflows
• Utilizing machine learning and deep learning techniques effectively
• Excelling in complex data analysis and predictive modeling
• Managing data pipelines and confirming data quality
• Leveraging programming languages such as Python, R, and MATLAB
• Embracing change and innovation in technology-driven environments