Senior AI/ML Architect

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About the Company

FinTech startup

agentic AI systems

banks and financial institutions

Job Overview

Senior AI/ML Architect

Key Responsibilities

AI Infrastructure Architecture:

• Design and implement asynchronous multi-agent orchestration systems.
  
• Manage end-to-end latency from user message to AI response.
  
• Build resilient inference pipelines that degrade gracefully under load.
  
• Implement intelligent request routing and load balancing for AI workloads.
  
• Migrate AI conversation flows from monoliths to microservices.
  
• Develop WebSocket/streaming infrastructure for real-time interactions.
  
• Design circuit breakers and fallback strategies for AI model failures.
  
• Implement observability and performance monitoring tools for AI systems.
  
• Optimize credit data retrieval and caching strategies.

Technical Requirements

Must-Have Experience:

• 6+ years of experience building production systems handling 10k+ concurrent users.
  
• Proven expertise in async/event-driven architectures (beyond REST APIs).
  
• Hands-on experience scaling ML/AI inference in production environments.
  
• Strong understanding of caching (Redis, in-memory, CDN).
  
• Experience with message queues and real-time communication protocols.
  

AI-Specific Expertise:

• Built and deployed systems integrating multiple LLM/AI models in production.
  
• Hands-on experience with AI model serving frameworks (TensorFlow Serving, Triton, etc.).
  
• Deep understanding of AI inference optimization (batching, caching, model quantization).
  
• Knowledge of conversation state management and context handling.
  
• Proven experience debugging production issues under high AI inference load.

Growth Path

• Direct impact on customer engagement and retention metrics.
  
• Opportunity to work on next-generation AI infrastructure challenges.
  
• End-to-end ownership of core technical and architectural decisions.
  
• Potential to lead the AI Platform team as the organization scales.