| Job Purpose | This role leads the domain strategy reasoning design and orchestration blueprint for Agentic AI use cases across the Risk Underwriting HR and RCU (Risk Control Unit) verticals. The position is responsible for translating credit policies underwriting rules HR process flows risk frameworks governance structures investigations logic and compliance checkpoints into machine-interpretable domain structures for autonomous agents. The role is central to driving trustworthy auditable domain-grounded reasoning and will anchor collaboration between business risk HR compliance and the Agentic AI tech teams to ensure accurate safe and production-ready agentic systems. |
| Duties and Responsibilities | Lead the end-to-end domain modelling reasoning architecture and orchestration logic for Agentic AI use cases across Risk Underwriting HR and RCU. Translate complex policy documents HR guidelines risk frameworks underwriting rules compliance playbooks and investigation workflows into structured reasoning frameworks rule engines and decision flows. Define agent-level guardrails constraint boundaries fallback behaviors escalation routes and risk thresholds for autonomous actions. Architect and maintain domain knowledge bases including credit heuristics personnel policies case-handling pathways risk scoring logic and RCU checks. Design thought-logging schemas reasoning trace structures and interpretability checkpoints to support audit compliance fairness and governance reviews. Collaborate closely with the Agentic AI tech team to integrate domain logic into agent frameworks multi-agent orchestration models and system APIs. Drive multi-layer testing scenario evaluation bias checks and reasoning audits to ensure agent reliability fairness and alignment to corporate standards. Partner with Credit Risk HR Payroll Talent Compliance Fraud/RCU and Investigations teams to continuously refine domain accuracy. Identify and prioritize new high-value use cases across the four verticals shaping the agent roadmap. Oversee documentation quality ensuring domain modules reasoning libraries orchestration guides and logic maps meet governance standards. Serve as the domain authority for internal stakeholders ensuring all agent behaviors remain compliant with policy regulatory norms and ethical AI guidelines |
| Key Decisions / Dimensions | Define reasoning architectures rule hierarchies and orchestration patterns for agentic workflows. Determine logging granularity interpretability depth and checkpoints required for governance. Approve fallback and escalation flows for sensitive cases in underwriting HR risk and investigations. Prioritize domain enhancements new initiatives and cross-functional integrations. Frame evaluation frameworks for agent reasoning: fairness accuracy stability compliance alignment |
| Major Challenges | Domain-Grounded Reasoning Design Translating implicit expert reasoning into explicit machine-executable decision frameworks. Managing uncertainty ambiguity and contradictory signals in domain data without oversimplifying. Interpretability Logging and Observability Designing logging schemas that support post-hoc reasoning audits without creating overhead or data bloat. Balancing performance with observability especially in production settings. Strategic Autonomy vs Control Deciding when agents should self-direct vs. escalate decisions to humans. Embedding guardrails that are both domain-relevant and adaptive under evolving agent capabilities. Feedback Loop Complexity Designing multi-layered feedback systems: self-reflection user feedback domain overrides model fine-tuning. Managing feedback prioritization: what gets logged analyzed and appliedand what gets ignored |
| Required Qualifications and Experience | Educational Qualifications 812 years of experience in Risk Underwriting HR Compliance RCU or related governance domains with exposure to AI or automation. Strong understanding of credit policy risk scoring frameworks HR SOPs RCU processes and compliance guidelines. Deep familiarity with decision systems rule engines case management workflows and governance processes. Working knowledge of Agentic AI frameworks LLM reasoning orchestration pipelines and interpretability best practices (preferred). Ability to translate policy-heavy content into structured auditable machine-executable logic. Excellent stakeholder communication cross-functional alignment skills and domain documentation ability. Strong analytical problem-solving and risk-awareness capabilities. |
Required Experience:
Senior IC
Lead AI UnitSenior Lead AI Unit • Pune, Maharashtra, India
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