Jobs · Engineering · Maryland

ERP AI Engineer - Manager

PwC · Baltimore, MD · 2 wk ago
HybridEngineering$99k–$232k/yrFull-time

About the role

As part of the Data and Analytics Engineering team, you will serve as both a technical leader and a trusted advisor to clients, combining AI/ML knowledge with business acumen to design and deliver AI solutions that drive measurable client outcomes. As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships, and translate complex business challenges into AI-driven strategies and solutions. This role offers the chance to shape AI solution architecture while driving innovation and excellence in client engagements.

Responsibilities

  • Lead and mentor teams of data scientists and ML engineers
  • Manage client relationships and promote satisfaction with deliverables
  • Translate intricate business challenges into AI-driven strategies
  • Design and implement AI solution architectures
  • Drive innovation and excellence in client engagements
  • Analyze data to derive actionable insights and solutions
  • Collaborate with stakeholders to align on project objectives
  • Uphold exceptional standards of quality and integrity in every task

Requirements

  • Bachelor's Degree
  • At least 7 years of experience in AI/ML engineering, data science, or a related technical role

Qualifications

  • Master's Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field preferred
  • Experience with Large Language Models and prompt engineering
  • Building scalable, cloud-native microservices and containerized deployments
  • Proficiency with MLOps tooling and CI/CD pipelines for ML
  • Experience with vector databases and semantic search architectures
  • Translating complex business problems into AI solution designs
  • Contributing to business development and proposal writing
  • Cloud certifications in AI/ML or solutions architecture preferred
  • Familiarity with Responsible AI principles and bias mitigation practices

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