almost 2 years ago
Bengaluru, IndiaSenior
Responsibilities
- Design and build scalable backend systems powering real-time enterprise AI Agents.
- Develop agent orchestration frameworks supporting multi-step reasoning, tool usage, and decisioning workflows.
- Build agent memory, context management, and state persistence systems across interactions.
- Architect low-latency inference pipelines integrating LLMs, SLMs, and external tools and services.
- Implement evaluation frameworks and continuous improvement loops for production AI agents.
- Design event-driven asynchronous workflows and optimize systems for throughput, latency, and cost-efficient inference.
- Build and maintain REST and gRPC APIs and service layers for agent capabilities.
- Partner with Applied AI and ML teams to productionize models and agent behaviors.
- Drive observability, monitoring, safety, guardrails, and architecture decisions for multi-tenant enterprise AI platforms.
- Collaborate with Product and Solutions teams to translate customer workflows into agentic systems.
Requirements
- At least 5 years of experience in backend engineering, distributed systems, or platform engineering.
- Strong experience building high-scale, production-grade backend systems.
- Experience with real-time processing, streaming, or event-driven architectures.
- Strong understanding of REST and gRPC API design and microservices architectures.
- Experience with SQL and NoSQL databases and high-scale data modeling.
- Hands-on experience with Docker, Kubernetes, and AWS, GCP, or Azure.
- Strong fundamentals in system design, concurrency, and performance optimization.
- Preferred experience with LLMs, conversational AI, or AI-powered products in production.
- Preferred familiarity with agent frameworks, tool calling, multi-step reasoning, RAG pipelines, vector databases, retrieval systems, and AI evaluation systems.
- Preferred understanding of prompting strategies, context windows, model behavior optimization, real-time decisioning systems, or workflow orchestration engines.
Benefits
- Competitive compensation with performance-based upside.
- Flexible vacation policy.
- Health insurance coverage.
- Globally distributed, high-impact team.
- Opportunity to build cutting-edge AI products at scale.
- Regular team offsites and in-person collaboration.
- Hybrid work model based in Noida, with 2–3 days per week in the office.
Tech Stack
Categories
About Level AI
Level AI builds a conversational intelligence platform for enterprise contact centers, combining speech AI, NLP, and retrieval to analyze customer interactions and drive QA, coaching, automation, and analytics. It sells its software to large customer service and sales teams, typically via subscription. Founded in 2018 and headquartered in Mountain View, the company is Series C–funded, with customers such as Wayfair, Smartsheet, Chime, Gusto, and Swiss Re.