The Role
Lead design and delivery of production-grade AI/GenAI services for underwriting, policy servicing, and claims. Architect multi-tenant LLM/RAG and decisioning platforms, enable document intelligence and omnichannel communications, integrate with insurance cores (Guidewire/Duck Creek), and establish insurance-grade MLOps/LLMOps. Build and scale an engineering team, prioritize roadmap by business outcomes (STP, leakage, TAT, loss ratio), and ensure observability, cost/latency SLOs, explainability, and auditability.
Summary Generated by Built In
You will lead the engineering of production‑grade AI/GenAI
services and agentic automations that uplift risk assessment, claims adjudication, and customer
communications on a secure, multi‑tenant foundation.
Key Outcomes & Engineering Responsibilities
● Own a 12–24‑month Insurance AI engineering roadmap across underwriting (L&A, P&C,
Specialty), policy servicing, and claims—prioritized by business outcomes (STP, leakage
reduction, TAT, loss ratio).
● Architect multi‑tenant AI services (LLM/RAG, risk/price models, adjudication engines) with
API‑first interfaces, strong tenancy isolation, observability, and cost/latency SLOs; enable
consumption by Insurance WorkDesk/agent portals and core ecosystems.
● Underwriting intelligence: ship services for submission ingestion, triage/prioritization, risk
scoring, quote‑acceptance prediction, and document summarization; integrate with rules
engines and rating/policy admin systems.
● Claims AI: deliver FNOL intake automation, AI triage, fraud/risk detection, and explainable
adjudication for Life, P&C, and Health; standardize salvage/subrogation sub‑processes and
omnichannel customer updates.
● Policy servicing & booking/binding: build GenAI‑assisted clause/wording libraries, template
governance, and contract generation with maker‑checker workflows and full audit trails.
● Agentic insurance journeys: operationalize multi‑agent frameworks (e.g., Underwriting
Assistant, Claim Adjudication) with guardrails (input/output filters, grounding, policy
catalogs) and human‑in‑the‑loop controls.
● Document intelligence (IDP): embed classification, extraction, and redaction for applications,
medicals, bills, loss evidence, and endorsements to reduce manual effort and errors.
● Customer communications: expose AI services that personalize and govern omnichannel
communications (renewals, endorsements, claim letters) with template control and
auto‑archival.
● Ecosystem integrations: design adapters for core platforms (e.g., Guidewire, Duck Creek),
CRM, and data‑partner APIs; package deployables for marketplace motions where
applicable.
● Establish insurance‑grade MLOps/LLMOps: model/data registries, offline/online evaluations
(grounding, fairness, leakage impact), CI/CD, blue‑green/canary rollouts, rollback, run‑books;
incident/SLA management.
● Build, coach, and scale a high‑performing team (applied science, ML/platform, evaluation &
safety); drive design rigor, reliability, and measurable production impact.
Requirements
● 10–12 years total; 5+ years leading AI/ML engineering teams shipping production AI in
insurance (L&A/P&C/Specialty) across underwriting, policy servicing, or claims.
● Systems design depth: multi‑tenant AI services, vector/feature stores, streaming ETL, event
architectures; observability and cost/performance optimization at scale.
● LLMs & decisioning: prompting, fine‑tuning, RAG; explainable decisioning aligned to
underwriting/claims policies; propensity, fraud, and price‑sensitivity models.
● Document AI & IDP: OCR/ICR + layout models for medical records, bills, proofs; privacy/PII
redaction; evidence packaging for audits.
● Domain fluency across Life & Annuity (policy issuance/underwriting, claims), P&C (policy
booking/binding, claims), and Health (auto‑adjudication, pre‑auth).
● Ecosystem experience with insurance cores/platforms (e.g., Guidewire, Duck Creek), CRM,
and data providers.
● Stakeholder leadership and communication; ability to explain model/platform trade‑offs to
executives, regulators, and customers.
Skills Required
- 10-12 years total experience with 5+ years leading AI/ML engineering teams shipping production AI in insurance (L&A/P&C/Specialty)
- Systems design depth for multi-tenant AI services, vector/feature stores, streaming ETL, and event architectures with observability and cost/performance optimization
- Experience with LLMs and decisioning: prompting, fine-tuning, RAG, and explainable decisioning aligned to underwriting/claims policies
- Document AI and IDP expertise: OCR/ICR, layout models, PII redaction, and evidence packaging for audits
- Domain fluency across Life & Annuity, P&C, and Health insurance processes (underwriting, policy issuance/binding, claims, auto-adjudication)
- Ecosystem experience integrating with insurance core platforms (Guidewire, Duck Creek), CRM systems, and data providers
- Stakeholder leadership and communication: explain model/platform trade-offs to executives, regulators, and customers
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The Company
What We Do
Marketscope is a technology company specializing in the development and integration of Advanced Driver Assistance Systems (ADAS) and the scaling of production-grade AI/ML applications. The company focuses on AI platform engineering and product stacks, targeting strategic enterprise accounts and government sales, particularly within the Indian market, while expanding its reach into new international industries.
