Role Description We’re looking for a Staff Enterprise AI Engineer focused on scaling internal operations across the business through AI-driven systems, agents, and workflow automation. This role designs and delivers secure, production-grade AI solutions that reduce manual work, increase productivity, and improve decision-making across all business functions while maintaining security and privacy. Success is measured by enterprise impact, not tool adoption. Key Responsibilities - AI Systems and Agent Architecture - Design and implement enterprise AI systems using Workato, MCP frameworks, Microsoft 365 Copilot, and Claude. - Build and orchestrate AI agents that automate cross-functional workflows across IT, Security, Finance, HR, Legal, Tech, and GTM. - Develop reusable patterns for agent orchestration, memory, context handling, and human-in-the-loop controls. - Enterprise Automation and Integration - Lead development of end-to-end automated workflows using Workato and related integration platforms. - Connect SaaS systems, data platforms, and internal services into unified AI-powered workflows. - Measurably reduce operational toil by eliminating repetitive manual processes. - AI Governance, Security, and Risk - Embed security, privacy, and compliance controls into AI systems by design. - Ensure alignment with SOC 2, ISO 27001, ISO 42001 and AI governance standards. - Define guardrails for data handling, prompt security, model access, and agent permissions. - Mitigate risks related to prompt injection, data leakage, model misuse, and over-automation. - Platform Enablement and Scale - Build internal AI capabilities that scale across teams, not one-off solutions. - Create reusable templates, SDKs, connectors, and playbooks for AI adoption. - Partner with IT, Security, and Enterprise Apps to operationalize AI at scale. - Productivity and Employee Experience - Leverage Microsoft 365 Copilot and Claude to enhance employee workflows. - Identify high-impact productivity use cases across departments. - Deploy AI assistants that meaningfully reduce time to complete core tasks. - Cross-functional Leadership - Partner with senior stakeholders to identify high-value AI opportunities. - Translate business problems into scalable AI solutions. - Influence roadmap, standards, and adoption strategy across 6sense. Qualifications - 7+ years in enterprise engineering, automation, or IT systems. - Hands-on experience building integrations and workflows using platforms like Workato or similar. - Experience with LLM-based systems including prompt design, agent orchestration, and tool usage. - Strong understanding of SaaS ecosystems and API-driven architectures. - Experience implementing security and compliance controls in cloud-native environments (AWS preferred). - Ability to operate at both deep technical and strategic levels. Preferred Qualifications - Experience with MCP or similar model context and agent frameworks. - Experience with Microsoft 365 Copilot extensibility and Graph API. - Experience with Claude or other enterprise LLM platforms. - Exposure to AI governance frameworks and responsible AI practices. - Background in scaling internal platforms in a high-growth SaaS company. Core Competencies - Systems thinking and platform design. - AI & Automation-first mindset. - Security and risk awareness in AI systems. - Strong technical judgment with bias for action. - Ability to simplify complex workflows through AI. Success Metrics - Reduction in manual workflows and operational overhead. - Measurable productivity gains across key functions. - Adoption and impact of reusable AI solutions across teams. - Compliance and risk posture of AI systems. - Time-to-value for new automation and AI initiatives. Example Impact Areas - AI agents that triage and resolve IT and security tickets. - Automated workflows for finance approvals, HR onboarding, and legal reviews. - Copilot-powered employee assistants integrated with enterprise systems. - Intelligent orchestration of data across SaaS platforms for decision support. Reporting Structure - Reports to: Head of IT and AI Transformation (Part of CISO/CIO org). What Good Looks Like - Ships production-ready AI systems and services, not prototypes. - Builds reusable capabilities, not isolated solutions. - Balances speed with security and governance. - Drives measurable business outcomes, not experimentation for its own sake. Benefits - Full-time employees can take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. - Access to equipment and support needed to work and connect with teams, at home or in one of our offices. - Growth mindset culture represented in onboarding and numerous learning and development initiatives including access to LinkedIn Learning platform. - Quarterly wellness education sessions to encourage self-care and personal growth. - Celebration of employee backgrounds through wellness days and ERG-hosted events.

• Sviluppare software in ambito AI, Generative AI e Agentic AI • Collaborare con il team su progetti innovativi e tecnologicamente avanzati • Raccogliere e analizzare requisiti di business • Progettare e implementare soluzioni software scalabili e performanti

Role Description Buscamos un(a) AI Engineer con experiencia en construcción y despliegue de soluciones basadas en agentes inteligentes, Backend y arquitecturas cognitivas. Este rol requiere conocimiento en frameworks de agentes y protocolos (Langchain, Llama, LLMs, NLP, A2A, MCP, etc.) y capacidades sólidas de software engineering para crear productos con IA embebida. Idealmente que tenga conocimiento en contextos financieros, contables, payroll, facturación o recursos humanos. Responsabilidades Principales - Experiencia desplegando y programando soluciones basadas en agentes inteligentes y LLMs, integrando herramientas como LangChain, LlamaIndex, AutoGen, CrewAI o frameworks equivalentes. - Implementar agentes que interactúan con usuarios, APIs, sistemas ERP o plataformas externas (e.g. WhatsApp, sistemas contables, CRMs). - Implementar arquitecturas MCP (Model Context Protocol) y A2A (Agent-to-Agent) para permitir coordinación multi-agente y flujos autónomos dentro de entornos empresariales. - Trabajar en ambientes productivos y con interacción directa con equipos de infraestructura, DevOps y MLOps. - Colaborar estrechamente con equipos de producto, UX, datos y backend para tener un delivery exitoso de las funcionalidades planeadas. - Implementar con buenas prácticas de desarrollo, validación y monitoreo de agentes, incluyendo tests de integración, control de versiones de prompts y trazabilidad de decisiones. - Mantenerse actualizado en frameworks de código abierto y papers relevantes en el campo de agent frameworks, memory architectures y multi-agent systems. Qualifications - 4-6 años de experiencia en proyectos de inteligencia artificial, con al menos 2+ años en implementación de agentes autónomos o copilts. - Experiencia comprobada utilizando frameworks como LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel o similares. - Conocimiento práctico de protocolos MCP y A2A, uso de herramientas, gestión de memoria y estado de conversación. - Sólido dominio de Python y experiencia con FastAPI, asyncio, Pydantic y arquitecturas asincrónicas. - Experiencia trabajando con vector stores (Chroma, Weaviate, Pinecone) y arquitecturas RAG. - Conocimiento en NLP, embeddings, agentes de recuperación, y funciones de razonamiento y planeación. - Conocimientos de MLOps: CI/CD, Docker, Kubernetes, monitoreo de agentes, y retraining automatizado. - Inglés técnico fluido para revisar documentación, papers y colaborar con equipos globales. Requirements - Experiencia en proyectos multicloud (Azure, AWS, GCP). - Familiaridad con arquitecturas orientadas a eventos y microservicios, así como APIs RESTful y gRPC. - Experiencia trabajando con datos empresariales en dominios como contabilidad, finanzas nómina, facturación o ERP. - Experiencia trabajando en equipos de desarrollo y producto así como en equipos de alto rendimiento/startups. - Conocimiento práctico de otros lenguajes como Golang, Java o C# (.NET), especialmente en la construcción de componentes de alto rendimiento. - Participación activa en comunidades de código abierto de agentes o contribuciones a frameworks emergentes. - Desarrollo de productos innovadores con enfoque en IA y datos. - Cultura de buenas prácticas, arquitectura moderna y trabajo colaborativo. - Posibilidades de crecimiento técnico y formación continua.

• Developing MCP-like tools that expose network device APIs and CLI commands with clear descriptions, structured inputs/outputs, validation logic, and error handling • Managing tool metadata and supporting semantic search over available tools using a vector database • Creating golden user queries, expected answers, and query variations for specific tools, intents, and network-operation scenarios • Building automated tests to verify correct tool selection, tool parameterization, output structure, and end-to-end agent responses • Designing evaluation workflows combining deterministic checks, human review, and LLM-as-a-judge techniques, for example using DeepEval or custom evaluation prompts • Refining prompts, tool descriptions, schemas, and agent workflows while monitoring regressions when new tools or changes are introduced • Developing production-quality Python code and tests using frameworks such as LangChain and LangGraph • Collaborating with software engineers, network domain experts, and DevOps teams to deliver reliable, testable, and maintainable agentic workflows