Stephen Bonifacio

Full-Stack Enterprise AI Agent

Designed and shipped a production-grade, multi-tenant LLM platform that augmented HR support workflows across multiple companies

• Modular, bring-your-own architecture (LLMs, vector DBs, tools, prompts)
• Async FastAPI backend optimized for concurrent RAG + tool execution
• Bespoke 'agent loop' implementation for full control and extensibility (parallel tool calls, custom retry logic, dynamic prompt injection, etc)
• Multi-tenant Next.js app with real-time streaming, branding, and isolation
• Enterprise-grade security: Entra ID SSO, 2FA, JWTs, encrypted PII storage
• Integrated ServiceNow (RAG + tickets) and SAP HCM (employee data access)
• Full observability with Langfuse (latency, tokens, evals, prompt versions)

Python • TypeScript • FastAPI • Next.js • Azure AI Search • Azure CosmosDB • Redis • Langfuse

Microsoft Teams Integration

Extended the core enterprise LLM platform into Microsoft Teams, enabling employees to access the same AI capabilities directly within their primary collaboration tool

• Implemented a Microsoft Teams bot as an additional frontend channel for the existing LLM platform
• Reused shared backend services, RAG pipelines, tools, and security model
• Built the bot using Microsoft Bot Framework and Express.js
• Integrated with Teams messaging APIs for real-time, bidirectional communication
• Implemented adaptive cards for structured, interactive responses in chat
• Deployed and managed via Azure Bot Service alongside the core platform

TypeScript • Express.js • Agent Framework • Azure Bot Service

Observability Platform for Admins

Built an internal observability and control plane enabling non-technical admins to operate, inspect, and improve production LLM systems

• Created document management interface enabling non-technical users to manage RAG knowledge base
• Built document ingestion pipeline for ServiceNow KM articles with automatic chunking and embedding
• Built conversation explorer with message logs, knowledge gap detection, and RAG pipeline inspection for admin oversight
• Implemented usage analytics dashboard tracking token consumption, tool usage, and peak engagement patterns
• Added ticket integration tracking and dark mode support

TypeScript • Next.js • shadcn/ui • Azure AI Search • Azure CosmosDB • Redis

Usage Analytics & Reporting Engine

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Designed an automated analytics and reporting engine providing executives and stakeholders with ongoing visibility into AI platform usage and value

• Built a scheduled reporting system delivering monthly AI usage reports via email
• Aggregated and deduplicated conversation data across all tenants and applications
• Generated insights covering cost trends, usage patterns, knowledge gaps, and top users
• Implemented fault-tolerant pipelines with automated error handling and retries
• Enabled month-over-month trend analysis to guide platform investment decisions

Python • Azure Functions • CosmosDB

AI-Powered Customer Experience (CX) Interviewer

Replaced a static customer experience survey with a conversational AI interviewer that probes each rating with dynamic follow-ups, capturing the qualitative "why" that traditional questionnaires miss

• Two-phase flow per question (score reasoning → what good looks like), independent state each
• Bounded AI: opener + 3 follow-ups, then graceful close — via versioned Langfuse prompts
• SSE streaming over Azure OpenAI SDK with a custom React hook for lifecycle management
• Full observability with Langfuse via OpenTelemetry (traces, tokens, prompt versions, sessions)
• Structured JSON logging with PII redaction, correlation IDs, and dev/prod level gating
• Server-side CosmosDB persistence (per-question docs, session-partitioned) behind Azure Easy Auth

TypeScript • Next.js 16 • React 19 • Azure OpenAI • Langfuse • Azure CosmosDB • Azure Easy Auth

Remote MCP Server for SAP HCM

Built a Model Context Protocol (MCP) server exposing SAP HCM employee data to the enterprise AI Agent for conversational access to personal, employment, timekeeping, and payroll records

• Single discriminated MCP tool covering four SAP HR domains — keeps the LLM's tool surface small and selection accurate
• Async FastMCP server over httpx with tenacity retries + exponential backoff for flaky SAP responses
• Per-domain parsers turning SAP's flat key-value payloads into structured, LLM-friendly output
• Azure Easy Auth flows the caller's identity into the SAP lookup, so each user sees only their own HR data
• Deployed on Azure App Service (streamable-http)
• Per-request correlation IDs and header-based client auth for enterprise traceability

Python • FastMCP • httpx • Tenacity • Azure App Service • Azure Easy Auth • Azure API Management • SAP HCM

DevOps & Infrastructure

Built and operated the CI/CD and cloud infrastructure underpinning all production AI applications

• Designed CI/CD pipelines in Azure DevOps for the backend API, web app, Teams bot, and admin app
• Automated build, test, and deployment workflows across dev, staging, and production
• Deployed services to Azure App Service with environment isolation and secrets management
• Standardized release processes to support frequent, low-risk deployments
• Supported rapid iteration while maintaining enterprise reliability requirements

Azure DevOps • Azure Pipelines • Azure App Service • Git • Bash

AI Architect

JG Summit Holdings Inc — Manila, Philippines
January 2023 – Present

Led the design and delivery of multiple production AI systems — including a multi-tenant LLM platform serving 4,000+ users — across a large enterprise group.

• Architected a modular, multi-tenant LLM platform serving 4,000+ users across business units
• Delivered a suite of AI applications: conversational HR agent, CX interviewer, Teams bot, admin control plane, and automated reporting pipeline
• Built enterprise integrations with ServiceNow, SAP HCM, and Microsoft Teams
• Owned full observability stack (Langfuse) and CI/CD infrastructure across dev, staging, and production
• Reduced HR response times from days to seconds and replaced static surveys with AI-driven CX interviews

Python • FastAPI • Next.js • TypeScript • Azure AI Foundry • Azure AI Search • Cosmos DB • Langfuse