About The Role

This role is about building the core infrastructure behind agentic AI.

You’ll work on the runtime, orchestration, memory, RAG, and tool execution systems that make multi-agent workflows reliable in production. This is deep backend and systems engineering—turning agent logic into scalable, secure, real-world platforms.

If you are curious about how agents actually work under the hood and want to build the backbone others depend on, we’d love to hear from you.

What You’ll Build

Agent runtime & orchestration (planning loops, execution, memory)
RAG pipelines and vector store integrations
Secure tool execution (sandboxing, policy enforcement)
Event-driven backend services (Text2SQL, workflows)
Multi-tenant SaaS + on-prem deployments
Observability: tracing, evals, token-level logging
Scalability & resilience: profiling, load testing, autoscaling
Open-source components and developer ecosystem

Must-Have Skills

Strong Python (production-grade)
Backend experience with FastAPI
MongoDB (data modeling, performance)
Docker and CI/CD fundamentals
AWS (core services, deployments)
Solid understanding of distributed systems & APIs

Nice to Have

Vector databases & embeddings
LLM providers, RAG systems
Text2SQL, tool calling, multi-agent systems
Azure or GCP exposure

How You Work

Product-first, extreme ownership
Strong systems thinking
Comfortable building from scratch
Research-driven but execution-focused
Care about correctness, scale, and safety

Engineering Levels

Core Engineer (2–3 yrs): Ship well-scoped features fast
Senior Core Engineer (3–6 yrs): Own major modules, mentor
Staff Core Engineer (5+ yrs): Architect systems, set standards

Why Lyzr

Build the backbone of the agentic era
Work on real agent infrastructure—not demos
Direct impact on how developers build AI systems