Senior AI Engineer – Insurance & AI Platform

Trantor Inc.; Bengaluru; Hybrid; INR 3,500,000 - 7,000,000; Full time

Job summary

Trantor Inc. in Bengaluru seeks a Senior AI Engineer to build GenAI-powered insurance platform features and scalable AI capabilities. You will design, ship, evaluate and scale production AI using LLMs, agentic workflows and intelligent document processing.

You will collaborate with Core Engineering, Product and Solutions teams to ensure reliable, cost-efficient AI services and drive quality, latency and performance improvements.

Qualifications

• Strong Python ownership and delivery of AI/ML applications.
• Experience with GenAI foundations, LLMs and agent workflows.
• Background in quality engineering for AI systems and guardrails.
• Hands-on Azure AI stack development and deployment.
• Familiarity with agent frameworks and orchestration tools.
• Experience with foundation models from major providers.
• Backend integration using REST APIs and databases.
• Exposure to DevOps and AI-assisted development tools.

Responsibilities

• Build GenAI solutions for insurance problems in production.
• Create agentic workflows with tool calling and orchestration.
• Automate document processing: classification, data extraction and summarisation.
• Select models and routing to balance quality, latency and cost.
• Set up evaluation suites and guardrails for reliable outputs.
• Tune systems for latency, token usage and scale.
• Integrate AI services with backend APIs and enterprise workflows.
• Mentor engineers and evolve engineering standards.

Skills

Python

GenAI (LLMs)

Quality engineering

Azure AI

Agent frameworks

Foundation models

REST APIs

Delivery tooling

Tools

Azure DevOps

GitHub Actions

Git

Docker

Claude Code

GitHub Copilot

PostgreSQL

Vector search

Job description

Senior AI Engineer – Insurance & AI Platform

Full Time

Experience: 6-10 years

Skills:

Hybrid

About the role

Join our core AI engineering team to build the intelligence behind our insurance technology platform. You will design, build, evaluate and scale production AI using generative AI, LLMs, agentic workflows and intelligent document processing, turning insurance business problems into dependable, measurable capabilities.

What you will do

• Build GenAI solutions for insurance. Design and ship production-grade LLM and generative AI features that solve real underwriting, claims and policy-servicing problems.
• Create agentic workflows. Develop AI agents with tool calling, orchestration and multi-step reasoning that can run reliably inside business processes.
• Automate document work. Build capabilities for document classification, data extraction and summarisation.
• Choose the right model. Assess various models from Azure AI define routing strategies that balance quality, latency, reliability and cost.
• Measure quality. Set up evaluation suites, structured outputs and guardrails, and run automated regression tests so quality stays visible as the product changes.
• Tune and operate. Optimise for latency, token usage and scale; monitor production systems and lead root-cause analysis when quality or performance slips.
• Integrate and collaborate. Connect AI services to backend APIs, databases and enterprise workflows alongside Core Engineering, Product and Solutions teams.
• Lead the team. Mentor AI engineers, shape engineering standards, and keep evaluating new models and frameworks for fit.

What you will bring

• Python and applied AI: strong hands-on delivery of AI/ML applications.
• GenAI foundations: LLMs, agents and function calling.
• Quality engineering: prompt design, structured outputs, guardrails, evaluation and AI observability.
• Azure AI stack: Azure AI, Microsoft Foundry and Azure OpenAI.
• Agent frameworks: Microsoft Agent Framework, LangGraph, Semantic Kernel or similar.
• Foundation models: working experience with OpenAI, Anthropic Claude or comparable providers.
• Backend skills: REST APIs, asynchronous processing, PostgreSQL (vector search is a plus).
• Delivery tooling: Git, Docker, CI/CD with Azure DevOps or GitHub Actions, and AI-assisted development tools such as Claude Code and GitHub Copilot.

Experience we are looking for

6-10 years in AI engineering, ML engineering, applied AI, or software engineering with substantial GenAI/LLM work.

• Proven production delivery: you have taken AI solutions from experiment and evaluation through deployment and monitoring, beyond prototypes.
• Engineering depth: solid grounding in system design, scalability and maintainability, with sharp analytical problem-solving.
• Nice to have: enterprise workflow experience and insurance domain knowledge.