Posted on: 28/05/2026
Description :
We are looking for an AI/ML Engineer to build and scale high-performance AI systems powering millions of real-time credit advisory interactions. The role involves working on LLM integrations, AI inference optimization, async architectures, and scalable AI infrastructure to deliver low-latency, resilient user experiences.
This is a high-impact opportunity to work on cutting-edge AI products and directly influence the financial journeys of millions of users across India.
What Youll Own :
AI Infrastructure Architecture :
- Design and implement asynchronous multi-agent orchestration
- Own end-to-end latency from user message to AI response
- Build resilient inference pipelines that gracefully degrade under load
- Implement intelligent request routing and load balancing for AI workloads
- Migrate critical AI conversation flows from monolith to dedicated services
- Implement WebSocket/streaming infrastructure for real-time chat
- Design circuit breakers and fallback strategies for AI model failures
- Build observability systems for AI performance monitoring
- Optimize credit data retrieval and caching strategies
What we are looking for :
- 3-5 years building production systems handling 10K+ concurrent users
- Strong experience with async/event-driven architectures
- Hands-on experience scaling ML/AI inference in production
- Deep understanding of Redis, caching, and CDN strategies
- Experience with message queues and real-time communication protocols
- Experience integrating multiple LLM/AI models in production
- Hands-on with AI model serving frameworks like TensorFlow Serving or Triton
- Knowledge of inference optimization techniques such as batching, caching, and quantization
- Strong understanding of conversation state management and context handling
- Experience debugging production issues under high AI inference load
Growth & Opportunity :
- Direct impact on customer retention through AI performance
- Exposure to cutting-edge AI infrastructure challenges
- Opportunity to lead and scale the AI platform team
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