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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and deploy agent-to-agent (A2A) communication architectures enabling autonomous agents to collaborate, delegate tasks, and execute multi-step business processes.
Integrate large language models (LLMs) with enterprise APIs and third-party SaaS applications to create multi-agent workflows with communication, information sharing, and task automation capabilities.
Manage cloud infrastructure (AWS, Azure, GCP) using Terraform and support DevOps practices including CI/CD pipelines, security, monitoring, and lifecycle management of multi-agent AI systems.
Minimum Requirements
Proven experience in integrating, fine-tuning, and optimizing foundation LLMs with expertise in prompt engineering and tool calling.
Hands-on experience building multi-agent systems, including inter-agent messaging, state management, and task delegation frameworks.
Advanced programming proficiency in Python or TypeScript for backend orchestration and API development.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Strong background creating scalable and secure multi-agent AI frameworks with knowledge of agent orchestration tools like LangChain, AutoGen, LangGraph, and tracing via LangSmith.
Experience with enterprise-grade AI integration including Retrieval-Augmented Generation (RAG), vector databases, and hybrid search architectures.
Familiarity with cloud DevOps and infrastructure automation (Terraform, Docker, Kubernetes) and security fundamentals for secure agent communications in enterprise environments.