Tax Platform Tech Lead - AI, Cloud & DevOps

PwC South Africa

Dallas (TX)

On-site

Confidential

Full time

14 days+

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Benefits offered by this job

Medical
Dental
Vision
401k
Holiday pay
Vacation
Personal and family sick leave

Job summary

PwC is seeking a Software Engineering Manager to lead one or more delivery teams focused on AI- and data-intensive tax platforms. You will drive architecture, guide implementation, and champion agile and DevOps practices to deliver scalable, cloud-native solutions.

You will mentor engineers, ensure quality outcomes, and collaborate across functions to meet client expectations and timelines, while promoting continuous improvement and responsible AI practices.

Qualifications

  • Bachelor's degree required.
  • At least 4 years of experience.
  • Experience leading software delivery teams.

Responsibilities

  • Lead delivery teams in design, build, and run of tax platforms.
  • Provide technical guidance and mentorship to team members.
  • Oversee architecture and implementation for quality outcomes.
  • Drive agile methodologies and DevOps practices within the team.
  • Collaborate with cross-functional teams to solve complex tax challenges.
  • Transform intricate tax issues into scalable, cloud-based solutions.
  • Foster a culture of continuous improvement and innovation.
  • Ensure alignment with project timelines and client expectations.

Skills

Team leadership
Mentorship
Agile methodologies
DevOps practices
Cloud platforms
CI/CD pipelines
AI and analytics
Effective communication

Education

Bachelor's Degree
Master's degree preferred

Tools

Cloud platforms
CI/CD tooling

Job description

PwC is seeking a Software Engineering Manager to lead one or more delivery teams focused on AI- and data-intensive tax platforms. You will drive architecture, guide implementation, and champion agile and DevOps practices to deliver scalable, cloud-native solutions.

You will mentor engineers, ensure quality outcomes, and collaborate across functions to meet client expectations and timelines, while promoting continuous improvement and responsible AI practices.

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