Product Engineer

Lyzr AI; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Lyzr AI, located in Bengaluru, is seeking a skilled software engineer to develop and maintain its core agent orchestration engine. Candidates should have 3-6 years of experience in backend development using Python and Go, alongside proficiency in developing and optimizing MongoDB systems.

The role involves working on real-time communication layers and cloud infrastructure on AWS, contributing to innovative AI solutions. We encourage applications from candidates with a passion for technology and a desire to drive meaningful business impact.

Qualifications

• 3-6 years of experience in backend development with Python and Go.
• Strong knowledge of MongoDB at scale and architecture.
• Experience with real-time communication protocols like WebSocket and SSE.

Responsibilities

• Build and maintain the core agent orchestration engine.
• Implement real-time communication for live agent interactions.
• Design and optimize MongoDB schemas for multi-tenant workloads.

Skills

Python (FastAPI)

Go

MongoDB

Next.js

AWS

WebSocket

Distributed systems

Tools

ECS

Redis

CloudWatch

Job description

Bangalore : On Site

Experience : 3-6 Years

About Lyzr

Lyzr is revolutionizing enterprise AI adoption with its cutting-edge Agent API Studio and Universal Agents. As winners of the Accenture Ventures 2024 GenAI Challenge, Lyzr is leading the charge in AI-driven business transformation. Our solutions empower organizations to leverage intelligent automation and drive meaningful impact.

What you'll do

Build and maintain the core agent orchestration engine, skill execution, and state management. Develop the builder UI in Next.js. Implement real-time communication layers (WebSockets, SSE) for live agent interactions. Own backend microservices in Python and Go. Design and optimize MongoDB schemas for multi-tenant, high-throughput workloads. Manage cloud infrastructure, deployments, and observability on AWS.

What we expect

• Backend — Python (FastAPI) and Go microservices at scale. WebSocket and SSE implementation, diagnosing socket-level issues.
• MongoDB at scale — sharding, indexing, replica sets. OAuth 2.0, JWT. Pub/Sub and event-driven architecture.
• Queue management, state persistence, retry and dead-letter handling. Latency, networking, and distributed systems performance.
• Frontend — Next.js. CSR vs SSR trade-offs. Hydration debugging. State management across client and server boundaries. Scalable component architecture. Reverse proxying and build optimization.
• Infrastructure — ECS, CloudWatch, VPCs, load balancers, security groups, DocumentDB, Redis, SigNoz or similar observability tooling.
• System Design — LLD (design patterns, SOLID, API contracts), HLD (distributed architecture, service decomposition, scalability, fault tolerance), database design (SQL & NoSQL schema modeling, indexing, query optimization, consistency trade-offs).

Nice to have

• AI agent frameworks
• LLM integration patterns (prompt chaining, function calling, structured outputs)
• Firecracker MicroVMs or E2B-style sandboxed execution
• agent memory and long-running task orchestration.