Senior Backend Engineer- AI Agents
TLDR
Build scalable backend systems for next-generation AI Agents that operate in real-time enterprise environments, enhancing operational efficiency and customer intelligence.
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
We'll love to explore more about you if you have:
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
Strong Plus (Agent / AI focus):
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
Perks & Benefits
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Competitive compensation with performance-based upside
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Flexible vacation policy
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Health insurance coverage
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Work with a globally distributed, high-impact team
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Opportunity to build cutting-edge AI products at scale
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Regular team offsites and in-person collaboration
Benefits
Flexible Work Hours
Flexible vacation policy
Health Insurance
Health insurance coverage
Team offsites
Regular team offsites and in-person collaboration
Level AI enhances customer engagement by transforming contact centers into strategic assets through an AI-native platform. By utilizing advanced technologies like Large Language Models, it extracts deep insights from customer interactions, providing organizations with actionable intelligence to improve customer experience and drive growth.