Quality Engineering Mts

Salesforce Salesforce · Enterprise · Mexico City, Mexico

This Quality Engineering role at Salesforce focuses on ensuring platform quality for AI CRM solutions, particularly in back-office and operational processes within financial services. The role involves developing QA protocols, collaborating with development teams, analyzing feedback, and identifying opportunities to use AI tools to improve efficiency and quality. While the company is AI-focused and uses AI tools, the core craft of this specific role is quality engineering and process improvement, not direct AI/ML model development.

What you'd actually do

  1. Develop and implement quality assurance protocols for software solutions, focusing on back-office and operational processes.
  2. Collaborate with software development teams to identify potential quality issues early in product design.
  3. Analyze user feedback and operational data to detect trends and areas for improvement in platform performance.
  4. Conduct regular audits of software functionalities to ensure they meet the necessary quality standards.
  5. Work closely with clients to understand process and quality requirements and tailor solutions accordingly.

Skills

Required

  • 2–5 years of experience in process automation, process improvement, or similar roles within Supply Chain or Financial Services environments, including finance, banking, insurance, asset management, or related sectors.
  • Strong understanding of process workflows and quality challenges in back-office or operational contexts.
  • Experience ensuring platform quality in operational processes.
  • Excellent analytical and problem-solving skills.
  • Strong communication skills to articulate complex problems and collaborate effectively with cross-functional teams.
  • A commitment to continuous learning and adaptation, including adopting new digital tools and AI solutions.
  • Proven ability to work effectively in a collaborative team environment.

What the JD emphasized

  • process automation
  • process improvement
  • platform quality
  • adopting new digital tools and AI solutions