AI Engineer - Multi-Agent Systems

About the job

Engineer with 5+ years of industry experience, out of which at least 3 years should be in AI, Enterprise RAG or Agents development (preferably Google ADK, but we can accommodate logical person with experience on other frameworks like Autogen / CREW AI / Microsoft Agents Framework etc.) • Agent Architecture & Development** • Design and implement multi-agent systems using Google ADK, including orchestrator agents, specialist agents, and tool-integrated agents for retail use cases • Define agent communication protocols, task decomposition strategies, and inter-agent coordination workflows • Integrate Google ADK agents with LLMs (Gemini), tools, APIs, and enterprise data sources • Build and maintain agent evaluation frameworks, safety guardrails, and fallback mechanisms • Exposure to RAG pipelines, vector databases (Vertex AI Search, Pinecone, Weaviate) • Knowledge of MLOps practices and Vertex AI model management on GCP • Enterprise Backend & Integration** • Develop and maintain microservices and APIs using Spring Boot / J2EE or .NET to power agent tool layers • Design RESTful and event-driven integration patterns connecting MAS to ERP, CRM, OMS, and POS systems • Implement secure, scalable data pipelines feeding real-time context to agents (inventory, pricing, customer data) • Ensure systems comply with enterprise standards: authentication (OAuth2/JWT), authorization, audit logging, and data governance • Technical Leadership** • Lead technical design reviews, architecture discussions, and code reviews for the MAS squad • Mentor junior and mid-level developers on AI agent patterns, enterprise best practices, and clean code principles • Collaborate with product managers, data scientists, and retail domain experts to translate business requirements into agent workflows • Define engineering standards, contribution guidelines, and CI/CD processes for the MAS platform • Retail Domain Delivery (good to have)** • Deliver AI agent solutions for retail verticals such as: smart replenishment, dynamic pricing, customer service automation, loyalty recommendation, and fraud detection • Work with retail stakeholders to define agent KPIs and build dashboards to monitor agent performance and ROI • Continuously improve agents through feedback loops, fine-tuning, and prompt engineering • Experience with retail-specific platforms: SAP Retail, Salesforce Commerce Cloud, Oracle Retail, or Manhattan • Familiarity with LangChain, LangGraph, AutoGen, CrewAI, or other OSS agent frameworks.

Requirements

• AI
• Google ADK
• APIs
• Microservices

Qualifications

• 5+ years of industry experience
• 3 years in AI

Preferred Technologies

• AI
• Google ADK
• APIs
• Microservices