Custom Software Engineer

Project Role : Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : SAP SuccessFactors Compensation, Generative AI

Good to have skills : NA

Minimum 3 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary

AI Powered Tech Talent You will design, configure, and enhance SAP SuccessFactors Compensation solutions while leveraging AI assisted development tools and copilots to accelerate requirement analysis, configuration, testing, documentation, and issue resolution. This role focuses on delivering efficient and compliant compensation planning cycles—merit, bonus, salary adjustments—while integrating pre built AI services to boost accuracy and productivity. No deep AI model development, vector DB work, RAG, or agentic AI capabilities are required.

Key Responsibilities

Compensation Functional & Technical Delivery

Configure and support SuccessFactors Compensation including:

• Salary Planning & Merit Cycles
• Bonus & Variable Pay Programs
• Guidelines, Budgets, and Eligibility Rules
• Worksheets, Templates, and Cycle Administration
• Compensation Statements & Approval Workflows
  
  
  

Use AI copilots to accelerate:

• Creation of functional specifications
• Rule and guideline validation
• Test case generation for planning cycles
• Documentation drafting (FS/TS/SOPs)
  
  
  

Deliver full lifecycle support—requirements, design, configuration, testing (SIT/UAT), go live, and hypercare.

Integrate Compensation with Employee Central, Performance & Goals, and Payroll (if applicable).

AI Assisted Productivity

Apply AI copilots to speed up:

• Requirement summarization
• Budget/spend analysis
• Rule analysis and what if checks
• Compensation cycle data validation
• Error pattern detection
  
  
  

Incorporate pre built AI services for:

• Intelligent employee grouping for planning (e.g., automated eligibility classification)
• Summarization of compensation insights (e.g., spend utilization, exception cases)
• Automated identification of anomalies during compensation cycles
  
  
  

Use LLM assisted troubleshooting to reduce turnaround time for configuration or cycle issues.

Governance, Compliance & Collaboration

Ensure compensation processes adhere to local/global policies, pay equity standards, compliance, and audit requirements.

Conduct workshops, solution walkthroughs, and cycle readiness reviews supported by AI generated insights.

Collaborate with Compensation & Benefits, HRBP, Performance Management, Payroll, and Technical Integration teams.

Contribute reusable templates, test packs, configuration documents, and AI augmented best practices.

Required Skills & Experience

SuccessFactors Compensation Expertise

Hands on experience with SF Compensation cycles including merit, bonus, and variable pay.

Understanding of guidelines, eligibility, budgets, templates, and statement generation.

Familiarity with integration points with EC, PMGM, and ECP.

AI Ready Skills

Experience using AI copilots, automated documentation tools, and AI assisted test accelerators.

Ability to integrate pre built AI capabilities into compensation planning processes (not custom AI model creation).

Understanding of responsible AI usage in HR and compensation contexts.

General Professional Skills

Strong analytical skills, especially in pay structures, budgets, and compensation compliance.

Ability to translate compensation strategies into scalable SuccessFactors configurations.

Effective communication, documentation, and stakeholder management skills.

Continuous learning mindset with openness to AI enabled workflows.

Good to Have

SuccessFactors Compensation / Variable Pay Certification.

Experience With Global Compensation Cycles And Localization Requirements.

Exposure to compensation analytics tools or pay equity platforms.

Familiarity with middleware tools (CPI/Boomi) for integrations.

Outcome Expectations

Deliver faster, more accurate compensation cycles using AI enabled productivity gains.

Improve budget utilization, pay accuracy, and planning transparency.

Act as a bridge between HR, Total Rewards teams, SAP engineering teams, and AI native experts when deeper AI support is required.

Additional information

A 15 years full time education is required., 15 years full time education

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