Senior Backend Engineer - AI Agents

Responsibilities

• Design and build scalable backend systems powering AI Agents that operate in real-time enterprise environments
• Develop agent orchestration frameworks (multi-step reasoning, tool usage, decisioning workflows)
• Build systems for agent memory, context management, and state persistence across interactions
• Architect low-latency inference pipelines integrating LLMs, SLMs, and external tools/services
• Implement evaluation (evals) frameworks to measure agent performance, accuracy, and reliability
• Enable continuous improvement loops (feedback → retraining → deployment) for AI agents in production
• Design and manage event-driven, asynchronous workflows for complex agent tasks
• Optimize systems for high throughput, low latency, and cost-efficient inference at scale
• Build and maintain robust APIs and service layers (REST / gRPC) for agent capabilities
• Partner closely with Applied AI / ML teams to productionize models and agent behaviours
• Collaborate with Product and Solutions teams to translate real customer workflows into agentic systems
• Drive best practices in observability, monitoring, safety, and guardrails for AI systems
• Contribute to architecture decisions for scaling multi-tenant, enterprise-grade AI platforms

Requirements

• 5+ years of experience in backend engineering, distributed systems, or platform engineering
• Strong experience building high-scale, production-grade backend systems
• Experience designing systems for real-time processing, streaming, or event-driven architectures
• Strong understanding of API design (REST, gRPC) and microservices architectures
• Experience with databases (SQL + NoSQL) and data modeling for high-scale systems
• Hands-on experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)
• Strong fundamentals in system design, concurrency, and performance optimization

Nice-to-Haves

• Experience working with LLMs, conversational AI, or AI-powered products in production
• Familiarity with agent frameworks, tool calling, or multi-step reasoning systems
• Experience building or integrating RAG pipelines, vector databases, or retrieval systems
• Exposure to evaluation systems (offline/online evals, A/B testing for AI systems)
• Understanding of prompting strategies, context windows, and model behavior optimization
• Experience with real-time decisioning systems or workflow orchestration engines