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

• Own and develop enterprise accounts across the Southeast (GA, FL, TN, NC, SC, AL) • Build 50%+ of pipeline through cold outreach, events, networking, and partner collaboration • Manage complex enterprise sales cycles ($75K-$200K ACV, 3-9 months) with multiple stakeholders • Sell to CIOs, COOs, CFOs, and operations leaders at manufacturers, financial institutions, and enterprise companies • Run discovery, demos, POCs, business case development, and contract negotiation • Partner with channel ecosystem to co-develop and accelerate opportunities • Maintain Salesforce CRM hygiene, pipeline accuracy, and quarterly forecasting • Travel across Southeast territory 20-40%

Role Description Senior Automation Engineers at Precisely design, build, and scale automation that connects tools, systems, and teams across globalization and user assistance operations. As a senior member of a global team, you work closely with engineers, information developers, localization specialists, DevOps, and other cross-functional stakeholders in an Agile, agentic-first environment. You lead the design and evolution of automation frameworks, reduce manual effort at scale, improve system reliability, and enable end-to-end workflows through API integrations, scripting, CI/CD, and AI-enabled automation. - Lead the design and implementation of automation supporting workflows across the documentation and software development lifecycle, including content creation, validation, publishing, UI localization, translation, and delivery. - Design, build, and operate production-grade agents, skills, scripts, and automation pipelines that replace complex, manual, and repetitive processes across documentation, localization, and language operations. - Architect and integrate systems across documentation, localization, and content platforms using MCPs and REST APIs to enable reliable, scalable, and secure end-to-end workflows. - Apply AI and LLM-based capabilities to generate, validate, transform, enrich, and manage content in alignment with approved security, privacy, and compliance standards. - Own the reliability, performance, and maintainability of automation systems through monitoring, troubleshooting, and continuous improvement. - Define and contribute to standards, patterns, and reusable components that support consistent and scalable automation practices. - Mentor team members through technical guidance, design reviews, and knowledge sharing. - Partner cross-functionally to advance automation maturity, innovation, and AI-assisted documentation and localization workflows. - Other duties may be assigned. Qualifications - BA/BS degree in computer science, engineering, information systems, or a related field, or equivalent practical experience. - 5+ years of experience in automation engineering, software engineering, or systems integration, preferably supporting developer platforms, documentation, localization, or content operations. - Strong proficiency in Python, with experience building maintainable, testable, production-grade automation and agent frameworks. - Advanced experience with Git-based workflows such as GitHub, including pull requests, code reviews, and repository automation. - Experience with work-tracking and planning tools such as Jira, Linear, or similar systems. - Strong understanding of CI/CD concepts and tools such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps. Requirements - Strong experience using AI-assisted engineering tools (e.g., GitHub Copilot, Cursor) with awareness of responsible AI practices including security, privacy, bias, and traceability. - Proven ability to design and operate production automation using Python and REST APIs. - Hands-on experience building and maintaining automation pipelines using Git-based CI/CD systems. - Demonstrated experience integrating LLMs via APIs to automate documentation and language operations. Preferred Skills - Experience designing or operating multi-agent or tool-orchestrated AI workflows at scale, including coordination and failure recovery. - Experience owning or evolving shared automation frameworks used across multiple products or teams. - Familiarity with observability, metrics, and cost tracking for AI-driven automation systems. - Experience containerizing, deploying, or operating long-running automation or agent services in production environments.