About Lyzr AI
Lyzr is building the foundation layer for agentic AI systems — making it radically simpler to build, deploy, and scale intelligent agents in production.
We believe the future of software is agent-first. Not wrappers. Not demos. Real systems that reason, act, observe, and improve over time.
We're looking for Core Engineers who want to work at the deepest layers of agentic infrastructure — the runtime, orchestration, memory, tool execution, and guardrails that power real-world AI systems.
If you're excited by how agents actually work under the hood, this role is for you.
What You'll Do
- Own end-to-end architectural decisions across backend services, frontend platforms, and infrastructure - ensuring systems are scalable, resilient, and cost-efficient.
- Define and champion engineering standards, design patterns, and architectural principles that teams actually want to follow.
- Lead architecture reviews - evaluate new proposals, identify risks early, and guide squads toward the right trade-offs.
- Drive backend excellence: microservices design, API contracts, data modelling, event-driven architecture, and performance at scale.
- Partner with frontend leads to shape component architecture, state management, and web performance standards across web and app.
- Collaborate with DevOps/SRE on cloud infrastructure, deployment strategies, observability, cost and reliability best practices.
- Act as a technical mentor - build architectural thinking and engineering craft across the organisation
- Translate product ambitions and growth targets into concrete technical roadmaps with clear Milestones.
- Lead AI-first architecture: ML Ops /LLM Ops, feature stores, vector search/RAG, real-time inference, evaluation/guardrails, responsible AI, model observability and governance
What We're Looking For
- 10 or more years of experience in software, cloud, or platform architecture leadership roles.
- Strong backend fundamentals; Python preferred
- Expertise in multi-tenant, distributed, microservices based systems on AWS, experience in Azure or GCP valued.
- Proven experience designing and governing high performance, high traffic digital platforms.
- Proven delivery of AI/ML and GenAI to production at scale (ML Ops/LLM Ops, guardrails, monitoring, governance)
- Experience with AI, machine learning, and automation for intelligent operations and observability.
- Familiarity with cloud networking, security, and cost optimization best practices.
- Security/compliance in regulated environments; privacy engineering and data governance
