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AI Architect - Multi Agent Platform

Leadsquared
5 - 8 Years
Bangalore

Posted on: 24/08/2026

Job Description

About the Role:

We're looking for an AI Architect to help design and scale the multi-agent platform that powers Lumen, Agent Studio, and Invorto. This role sits at the intersection of deep technical architecture and real-world production systems, you'll be responsible for the design decisions that determine how reliably, efficiently, and securely our agentic AI systems operate at scale.

What You'll Do:

- Architect and design multi-agent platforms and systems that operate reliably at production scale.

- Define the technical approach for retrieval-augmented generation (RAG), vector search, and knowledge grounding across our AI products.

- Set architectural standards for LLM orchestration, agent-to-agent communication, tool use, memory, and reasoning pipelines.

- Evaluate and select the right vector databases, retrieval strategies, and model choices for different product needs.

- Partner closely with engineering teams to translate architecture into production-grade, scalable implementations.

- Drive decisions on system reliability, latency, cost, and security for AI-driven workflows used by enterprise customers.

- Work directly with customers and internal stakeholders to understand requirements and ensure the architecture supports real-world business use cases.

- Stay hands-on - prototyping, reviewing code and designs, and solving hard technical problems alongside the team.

- Keep the architecture current with the fast-evolving LLM and agentic AI landscape.

What We're Looking For :

- 5 to 8 years of experience in software/AI engineering, with demonstrated experience designing and architecting multi-agent platforms at production grade.

- Strong hands-on expertise in Python.

- Deep understanding of LLMs - prompting, fine-tuning, evaluation, and production deployment considerations.

- Practical experience with RAG architectures and vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS, or similar).

- Proven experience taking AI systems from design to production at scale, with a strong focus on reliability and performance.

- Strong system design skills, with the ability to make sound architectural trade-offs in a fast-moving environment.

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