Custom Software Engineer

Project Role :Custom Software Engineer


Project Role Description :Design, build and configure applications to meet business process and application requirements.
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
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:
oSalary Planning & Merit Cycles
oBonus & Variable Pay Programs
oGuidelines, Budgets, and Eligibility Rules
oWorksheets, Templates, and Cycle Administration
oCompensation Statements & Approval Workflows
Use AI copilots to accelerate:
oCreation of functional specifications
oRule and guideline validation
oTest case generation for planning cycles
oDocumentation 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:
oRequirement summarization
oBudget/spend analysis
oRule analysis and what if checks
oCompensation cycle data validation
oError pattern detection
Incorporate pre built AI services for:
oIntelligent employee grouping for planning (e.g., automated eligibility classification)
oSummarization of compensation insights (e.g., spend utilization, exception cases)
oAutomated 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.
Qualification15 years full time education