C&G CONSULTING SERVICES, INC. is hiring: AI developer with machine learning expe

Salary: $135,200 - 176,800 per year Requirements: A minimum of 5 years of professional experience in AI development and deployment, particularly with Generative AI and Conversational AI. Extensive practical experience with AWS Bedrock, focusing on the deployment and integration of various Foundation Models (FMs). Proven ability in utilizing AWS Q for code generation, analysis, and integration within development workflows, particularly pertaining to AI applications. Comprehensive understanding of diverse Generative AI models (text, image, etc.) and techniques in Conversational AI (dialogue management, intent recognition, entity extraction). Demonstrated skill in evaluating and selecting AI models and conversational AI platforms based on specific needs and performance metrics. Strong experience with AWS AI/ML services (e.g., SageMaker, Comprehend, Translate, Polly, Lex) and their application in Generative and Conversational AI solutions. Solid grasp of prompt engineering techniques to elicit desired outputs from Large Language Models (LLMs) and to design effective chatbot interactions. Experience in fine-tuning pre-trained models and customizing conversational AI agents for specific tasks and domains is highly desirable. Preferred experience in crafting and deploying AI chatbots or conversational agents using platforms like Amazon Lex, Dialogflow, Rasa, or similar. Familiarity with School Information Systems (SIS), Learning Management Systems (LMS), and education technology frameworks, including data structures and integration methods, is a significant advantage. Proficiency in API development (RESTful, GraphQL), automation workflows, and event-driven architectures. Extensive experience with cloud-native development and deployment on AWS, incorporating serverless technologies (AWS Lambda). Excellent problem-solving abilities, critical thinking skills, and the capacity to translate educational needs into effective AI and conversational solutions. Strong collaboration and communication skills for effective teamwork with AI/ML engineers, data scientists, educators, and administrators. Understanding of data privacy, security best practices, and compliance standards (e.g., FERPA) related to AI and chatbot applications. Experience with MLOps practices for deploying, monitoring, and maintaining AI models and conversational agents in operational environments. Responsibilities: Design, develop, and implement Generative and Conversational AI solutions, leveraging AWS Bedrock, AWS Q, and related AWS services to integrate with school systems (SIS, LMS, student data platforms, and assessment tools). Engineer and execute integrations with standard SIS

In Summary: A minimum of 5 years of professional experience in AI development and deployment, particularly with Generative AI and Conversational AI . Strong experience with AWS Bedrock, focusing on the deployment and integration of various Foundation Models (FMs) Preferred experience in crafting and deploying AI chatbots or conversational agents using platforms like Amazon Lex, Dialogflow, Rasa or similar .

En Español: Salario: $135,200 - 176,800 por año Requisitos: Un mínimo de 5 años de experiencia profesional en el desarrollo y implementación de IA, particularmente con AI generativa y conversacional. Extensa experiencia práctica con AWS Bedrock, centrándose en la implantación e integración de varios Modelos Fundamentales (FMs). Capacidad probada para utilizar AWS Q para generación de código, análisis y integración dentro de los flujos de trabajo del desarrollo, especialmente relacionados con las aplicaciones de AI. Comprensión integral de diversos modelos de AI Generativo (texto, imagen, etc.) y técnicas de AI Conversacional (gestión de diálogo, reconocimiento de intenciones, extracción de entidades). Familiarización con los Sistemas de Información Escolares (SIS), sistemas de gestión del aprendizaje (LMS) y marcos tecnológicos educativos, incluidas las estructuras de datos y métodos de integración, es una ventaja significativa. Proficiencia en el desarrollo de API (RESTful, GraphQL), flujos de trabajo de automatización y arquitecturas impulsadas por eventos. Extensa experiencia con el desarrollo nativo de la nube y su implementación en AWS, incorporando tecnologías sin servidor (AWS Lambda). Excelentes habilidades para resolver problemas, habilidades de pensamiento crítico y capacidad para traducir las necesidades educativas en soluciones eficaces de IA y conversaciones. Fuertes competencias de colaboración y comunicación para un efectivo trabajo en equipo con ingenieros AI/ML, científicos de datos, educadores y administradores. Comprensión de privacidad de los datos, mejores prácticas de seguridad y normas de cumplimiento de los estudiantes (por ejemplo, FERPA) relacionadas con AWS SIS y chatbot.