• Build and maintain the training and inference pipelines for character AI agents, including LLM/SLM orchestration and swarm-based architectures • Deploy and operate AI agents across social media platforms (Instagram, X, WhatsApp, TikTok) with consistent character behavior and personality coherence • Develop tooling for studios and creators to customize agent personality, lore, brand guidelines, and behavioral guardrails • Build and improve the feedback loops — fine-tuning, reward models, RLHF, and RLAIF — that keep agents improving over time • Architect and scale the infrastructure supporting agent deployments, including multi-modal capabilities (text, voice, video, livestreaming) • Contribute to the agentic commerce platform — enabling agents to drive transactions, recommend products, and interact with payment systems • Implement safety and content moderation systems to ensure agents behave appropriately across diverse user interactions • Collaborate with studio partners to translate creative direction into agent training parameters and behavioral specifications • Monitor agent performance, engagement metrics, and behavioral drift in production

• Provide technical leadership for the AI Platform squad, defining architecture, standards, and best practices to deliver AI services and provide access to corporate data for multiple teams across the company. • Define and evolve the AI Platform architecture • Lead the team technically (code reviews, design reviews, technical direction) • Establish standards for: • Internal APIs • API governance • Security and access to sensitive data • Observability and scalability • Work on integrating AI models and LLMs • Design solutions based on MCP (Model Context Protocol) • Ensure information security best practices and compliance (LGPD) • Act as a bridge between technical and strategic teams • Support stack decisions and technological evolution

• Deploy and configure agentic AI workflows and AI-powered automations within client ServiceNow environments. • Translate customer business requirements into technical architectures and implementation plans. • Implement and integrate NewRocket Agent Packs and AI solutions into enterprise environments. • Work directly with customers to tailor AI solutions to their operational workflows and business processes. • Build demos, prototypes, and proof-of-concept implementations to validate AI-driven workflows with clients. • Rapidly iterate solutions with customers to refine AI-powered use cases. • Support implementation of AI orchestration, LLM integrations, and agentic decision models. • Develop integrations between ServiceNow, enterprise systems, APIs, and AI services. • Build supporting components such as scripts, microservices, automation logic, and integration services. • Implement integrations with AI platforms, APIs, and enterprise data sources. • Actively contribute to the development and evolution of NewRocket’s AI intellectual property and platforms.

Role Description We are seeking Senior AI Agent Engineers to lead the development and deployment of enterprise-grade AI agents. This is a high-impact, execution-focused role where you will be responsible for moving from architectural design to a fully functioning Minimum Viable Product (MVP). You will build autonomous and semi-autonomous agents that interact with the Microsoft 365 ecosystem and proprietary data via the Azure AI Foundry agent service. Technical Objectives (The "How") - Agentic Orchestration: Design and deploy sophisticated agents using the Microsoft AI Foundry agent service and the Microsoft Agent Framework. - Data Integration: Leverage Azure AI Document Intelligence for complex data extraction and Azure AI Search for advanced RAG (Retrieval-Augmented Generation) indexing. - Ecosystem Connectivity: Build secure, OAuth-based integrations using the Microsoft Graph API to allow agents to interact with M365 (Teams, SharePoint, Outlook). - Production Python: Develop clean, scalable, and async-capable Python code for agent logic, tool calling, and custom API connectors. Key Responsibilities - Architect and build multi-agent workflows that can plan, reason, and execute tasks autonomously. - Implement Identity and Security protocols (Microsoft Entra ID) to ensure agents operate within enterprise compliance boundaries. - Develop the full lifecycle of the MVP: from local development and prompt engineering to cloud-hosted deployment and monitoring. - Integrate structured and unstructured data sources into agent memory using vector databases and AI Search. Qualifications - 5+ years of Senior Software Engineering experience, with at least 2 years focused on Generative AI and LLM orchestration. - Proficient in Python and deeply familiar with the Azure AI / Microsoft AI stack. - Proven experience with Microsoft Graph API and handling complex enterprise permissions. - Experience with LangGraph, Semantic Kernel, or the new Microsoft Agent Framework is highly preferred. Requirements - You don't just "research"—you build. You have a track record of deploying functional AI products to production. Benefits - 100% Remote - Holidays off - Paid Time Off - Health insurance assistance program - Competitive USD compensation - Strong team culture and collaborative environment - Ongoing training and growth opportunities