We are looking for a hands-on Lead Full-Stack AI Agent Engineer to drive the technical development of an enterprise-grade multi-agent AI platform and a suite of analytical AI agents for the Finance & Accounting domain. In this role, you will lead the engineering of a production-ready agentic platform built on Microsoft Azure and Microsoft Foundry, combining LLM-based reasoning, deterministic business logic, and statistical anomaly detection to deliver reliable, secure, and scalable AI-driven analytical solutions. This is not a traditional chatbot or document-based RAG development role. You will be responsible for building the core agentic infrastructure, including orchestration, shared memory, model routing, security mechanisms, and reusable agent architecture, as well as developing specialized analytical agents. You will combine hands-on engineering with technical leadership, setting engineering standards, guiding developers, and ensuring production readiness. Responsibilities Technical Leadership: Lead a dedicated AI engineering team, provide hands-on technical guidance, conduct code reviews, establish engineering standards, and develop reusable agent templates and architectural patterns Multi-Agent Platform Development: Design and implement the core agentic architecture, including the Master Orchestrator, Agent Registry, multi-LLM routing (Claude and Azure OpenAI), and multi-level caching mechanisms (Redis and prompt caching) Context and Memory Management: Develop shared context and memory services to manage domain glossaries, business rules, analytical thresholds, and persistent user feedback. Implement mechanisms that allow agents to retain user confirmations, dismissals, and false-positive suppression rules AI-Powered Analytical Workflows: Build specialized analytical and control agents that work with structured financial and ERP data. Combine deterministic business rules, Python-based statistical anomaly detection, and LLM-generated explanations supported by data references and citations Enterprise Security and Governance: Implement secure identity propagation using Microsoft Entra ID and On-Behalf-Of (OBO) flows, Role-Based Access Control (RBAC), and row-level security. Ensure data freshness, traceability, and reliable citation mechanisms to prevent unsupported AI-generated insights and unauthorized data access Observability and Production Support: Implement operational and business KPI monitoring, build telemetry dashboards, lead production releases, and support hypercare activities and knowledge transfer to the client's IT team Requirements Strong Python Backend Engineering: Advanced experience with Python 3.11+, asyncio, FastAPI, Pydantic v2, pytest, strict typing, and clean, modular software architecture Production-Grade Agentic AI Development: Hands-on experience designing and implementing multi-agent AI systems using Microsoft Foundry (Azure AI Agent Service), Semantic Kernel, LangGraph, or AutoGen. Understanding of orchestrator–subagent patterns, MCP (Model Context Protocol), and structured tool calling State Management and Caching: Production experience with Redis for session management and semantic caching, as well as PostgreSQL, Cosmos DB, or similar databases for persistent agent memory, audit logs, and user feedback Azure Security and Identity Management: Practical experience with Microsoft Entra ID (Azure AD), OAuth 2.0 On-Behalf-Of (OBO) flows, RBAC, and Azure Key Vault LLMOps and Observability: Experience with OpenTelemetry, Azure Application Insights, Langfuse or Microsoft Foundry tracing, prompt caching, and LLM token usage and cost optimization Nice to have Experience developing AI-driven solutions for Finance, Accounting, Audit, or ERP analytics Experience integrating AI applications with Microsoft Fabric or enterprise SQL data warehouses Experience designing enterprise-grade AI platforms with a focus on scalability, security, governance, and performance
