About this role
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
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