AI Engineer

GoDigit; Bengaluru; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

Go Digit General Insurance Limited in Bengaluru is seeking a Software Engineer - AI Engineering to independently build and deliver complex AI solutions as a key contributor within an AI delivery pod.

You will own critical modules, work with LLMs, RAG, Agentic AI, MCP, Voice AI, CV, and Intelligent Document Processing technologies, and mentor junior engineers while driving performance, scalability, and production readiness.

Qualifications

• 2–3 years of experience in Software Engineering, AI/ML Engineering, or GenAI solution development.
• Experience building and deploying production-grade applications.
• Strong expertise in Python and backend application development.
• Experience with LLMs, RAG, Prompt Engineering, Agentic AI, or AI integrations.
• Experience with FastAPI, LangChain, LangGraph, APIs, and Microservices.
• Understanding of distributed systems, SQL, CI/CD, Docker, and cloud platforms.
• Strong debugging, optimization, and production support capabilities.
• Ability to independently own and deliver complex technical implementations.

Responsibilities

• Design and develop complex AI applications, services, APIs, and integrations.
• Build scalable solutions using LLMs, RAG, Agentic AI, MCP, Voice AI, Computer Vision, and Intelligent Document Processing technologies.
• Own and deliver critical modules and technical components.
• Contribute to technical design discussions and solution implementation.
• Review code and support engineering quality initiatives.
• Mentor and support junior engineers on design, coding, and debugging practices.
• Optimize applications for performance, scalability, reliability, and maintainability.
• Build reusable frameworks, libraries, and accelerators.
• Support production releases, monitoring, troubleshooting, and root-cause analysis.
• Collaborate with Technical Leads on solution execution and sprint delivery.

Skills

Python

Backend development

Distributed systems

CI/CD

Debugging

Mentoring

Tools

FastAPI

LangChain

LangGraph

APIs

Microservices

Job description

Company: Go Digit General Insurance Limited
Location: Bengaluru
Work Mode: #LI-On-site, five days a week

About the Role

We are looking for a Software Engineer - AI Engineering to independently build and deliver complexAI solutions while serving as a key technical contributor within an AI delivery pod.

This role requiresstrong development expertise, ownership of critical modules, and the ability to driveimplementations with minimal supervision.

Key Responsibilities

1. 1. Design and develop complex AI applications, services, APIs, and integrations.
2. 2. Build scalable solutions using LLMs, RAG, Agentic AI, MCP, Voice AI, Computer Vision, andIntelligent Document Processing technologies.
3. 3. Own and deliver critical modules and technical components.
4. 4. Contribute to technical design discussions and solution implementation.
5. 5. Review code and support engineering quality initiatives.
6. 6. Mentor and support junior engineers on design, coding, and debugging practices.
7. 7. Optimize applications for performance, scalability, reliability, and maintainability.
8. 8. Build reusable frameworks, libraries, and accelerators.
9. 9. Support production releases, monitoring, troubleshooting, and root-cause analysis.
10. 10. Collaborate with Technical Leads on solution execution and sprint delivery.

Required Experience

1. 1. 2-3 years of experience in Software Engineering, AI/ML Engineering, or GenAI solutiondevelopment.
2. 2. Experience building and deploying production-grade applications.
3. 3. Strong expertise in Python and backend application development.
4. 4. Experience with LLMs, RAG, Prompt Engineering, Agentic AI, or AI integrations.
5. 5. Experience with FastAPI, LangChain, LangGraph, APIs, and Microservices.
6. 6. Understanding of distributed systems, SQL, CI/CD, Docker, and cloud platforms.
7. 7. Strong debugging, optimization, and production support capabilities.
8. 8. Ability to independently own and deliver complex technical implementations.

Success Measures

1. 1. Successful delivery of complex AI capabilities.
2. 2. High engineering quality and maintainability.
3. 3. Contribution to reusable frameworks and shared components.
4. 4. Effective mentoring support within the pod.
5. 5. Reliable, scalable, and production-ready solutions.
6. 6. Contribution to engineering standards and technical excellence