Job Title: Process Trainer Life Insurance

Position Overview

We are looking for a knowledgeable, agile, and engaging Process Trainer to join our Learning & Development (L&D;) team within the Life Insurance division. In this role, you will be responsible for designing, delivering, and evaluating end-to-end training programs for current hires and existing employees across customer support, operations, and sales channels.

Your primary focus will be translating complex life insurance products, regulatory guidelines, policy servicing workflows, and underwriting rules into transparent, actionable, and engaging training modules.
Department: Learning & Development (L&D;)
Location: Hyderabad
Experience Level: Mid-level [must have 36 years of experience in insurance process training]

Key Responsibilities

Training Delivery & Facilitation
New Hire Onboarding: Conduct structured Induction & NHT (New Hire Training) batches covering foundational insurance concepts, company products, systems, and process workflows.
Refresher & Upskilling: Identify process gaps, audit accuracy,



and deliver targeted floor support or refresher training sessions to boost operational efficiency and quality scores.
Regulatory & Compliance Training: Ensure all trainees thoroughly understand local insurance regulations [e.g., IRDAI / regulatory guidelines], anti-money laundering (AML) policies, data privacy laws, and ethical selling practices.

Content Development & Knowledge Management
Module Design: Create and continuously update training manuals, presentation decks, Standard Operating Procedures (SOPs), process maps, job aids, and interactive assessments.
Product Mapping: Translate technical life insurance products (Term Plans, ULIPs, Endowments, Annuities, Riders) into easy-to-understand training collateral.
Process Change Management: Stay up to date with product modifications, underwriting updates, and system enhancements, ensuring all training materials reflect live operational standards.

📌 Process Trainer Hyderabad
🏢 PolicyBazaar
📍 Hyderabad