AI Developer

Architect, develop, and deploy Generative and Conversational AI-powered solutions, primarily leveraging AWS Bedrock, AWS Q, and related AWS services, to integrate with school systems (SIS, LMS, student data platforms, and assessment tools).

Design and implement integrations with common SIS & LMS platforms (e.g., PowerSchool, Infinite Campus, Blackbaud, Canvas, Moodle, Google Classroom, Microsoft Teams for Education) to enable AI-driven enhancements and intelligent conversational interfaces.

Develop robust middleware, APIs, and automation scripts to facilitate seamless communication and data exchange between AI models, conversational agents, and school infrastructure.

Build, deploy, and manage secure and scalable RESTful APIs, GraphQL APIs, and Webhooks to enable real-time interaction with AI services and chatbot functionalities.

Design and implement efficient data pipelines (ETL/ELT) using AWS services (e.g., Glue, Step Functions) to prepare and deliver data for AI model consumption and output integration, as well as to inform and train conversational AI agents.

Develop and deploy AI-powered features such as intelligent content generation, automated summarization, personalized learning recommendations, advanced data analysis, predictive insights, and intelligent chatbots for student support, administrative assistance, and enhanced learning experiences using AWS Bedrock models and conversational AI platforms.

Utilize AWS Q to accelerate development tasks, including code generation, debugging, and understanding AWS best practices, particularly in the context of building AI-powered conversational interfaces.

Implement and manage knowledge bases and retrieval augmented generation (RAG) systems using AWS Bedrock capabilities to enhance the accuracy and contextuality of AI outputs and chatbot responses.

Design and develop engaging and effective conversational flows for AI chatbots, considering user experience best practices.

Ensure secure and compliant data handling in all AI and chatbot applications, adhering to FERPA and other relevant regulations.

Implement robust authentication and authorization mechanisms (OAuth 2.0, SAML, JWT) for AI and chatbot integrations within the AWS environment.

Collaborate closely with AI/ML engineers and data scientists to evaluate model performance, fine-tune models, optimize AI pipelines, and improve the effectiveness of conversational agents.

Work with DevOps teams to deploy and monitor AI applications and chatbots on AWS, utilizing serverless functions (AWS Lambda) and event-driven architectures (AWS EventBridge).

Collaborate with educators and administrators to understand their needs, identify opportunities for AI-driven innovation, including intelligent chatbots, and translate those into technical requirements.

Develop comprehensive documentation for AI solutions and chatbots, including architecture diagrams, API specifications, conversational flow designs, and deployment guides.

Stay up-to-date with the latest advancements in AI, particularly within the AWS ecosystem and in the field of Conversational AI, and proactively recommend new tools and techniques.

Do you have experience in Systems integration?, AI Developer with a strong focus on both Generative and Conversational AI to build and deploy intelligent solutions that seamlessly integrate with our educational systems. This role demands deep expertise in leveraging various AI models, with a significant emphasis on AWS Bedrock and AWS Q, as well as experience in developing AI chatbots and conversational agents. You will be instrumental in connecting these advanced AI capabilities with our existing School Information Systems (SIS), Learning Management Systems(LMS), and other educational technologies to optimize school operations, enhance learning experiences, provide valuable insights, and create engaging conversational interfaces. The ideal candidate will have a proven track record in developing and deploying a range of AI applications, including those utilizing Large Language Models (LLMs), Generative AI, and Conversational AI frameworks. Extensive experience with AWS cloud services is essential, with specific expertise in AWS Bedrock, AWS Q, and related AI/ML services being highly valued.

Familiarity with the education technology landscape and a passion for applying AI to solve real-world educational challenges, including creating intelligent chatbots for educational purposes, are significant advantages. You should be adept at designing, building, and deploying scalable and secure AI-powered workflows and conversational interfaces.

Requirements:

Minimum of 5 years of professional experience in AI development and deployment, with a strong emphasis on Generative AI and Conversational AI. Extensive hands-on experience with AWS Bedrock, including deploying and integrating various Foundation Models (FMs).

Demonstrable experience utilizing AWS Q for code generation, analysis, and integration within development workflows, particularly in the context of AI applications.

Deep understanding of different Generative AI models (text, image, etc.) and Conversational AI techniques (dialogue management, intent recognition, entity extraction). Proven ability to evaluate and select appropriate AI models and conversational AI platforms based on specific requirements and performance metrics.

Strong experience with AWS AI/ML services (e.g., SageMaker, Comprehend, Translate, Polly, Lex) and their integration with Generative and Conversational AI models.

Solid understanding of prompt engineering techniques for eliciting desired outputs from LLMs and designing effective chatbot interactions.

Experience with fine-tuning pre-trained models and customizing conversational AI agents for specific tasks and domains is highly desirable.

Preferred experience in developing and deploying AI chatbots or conversational agents using platforms like Amazon Lex, Dialogflow, Rasa, or similar.

Familiarity with SIS, LMS, and education technology platforms, including data structures and integration methods, is a significant plus.

Strong proficiency in API development (RESTful, GraphQL), automation workflows, and event-driven architectures.

Extensive experience with cloud-native development and deployment on AWS, including serverless technologies (AWS Lambda).

Excellent problem-solving skills, critical thinking, and the ability to translate educational needs into effective AI and conversational solutions.

Strong collaboration and communication skills to work effectively with AI/ML engineers, data scientists, educators, and administrators.

Understanding of data privacy, security best practices, and compliance requirements (e.g., FERPA) in the context of AI and chatbot applications.

Experience with MLOps practices for deploying, monitoring, and maintaining AI models and conversational agents in production., Generative AI Platforms: AWS Bedrock (Anthropic Claude, AI21 Labs Jurassic,

Stability AI, etc.), AWS Q

Conversational AI Platforms: Amazon Lex, Dialogflow, Rasa (preferred)

AI/ML Services (AWS): AWS SageMaker, Amazon Comprehend, Amazon Translate,

Amazon Polly, Amazon Kendra

Programming Languages: Python (expert level proficiency required), Node.js

API Development: RESTful APIs, GraphQL, API Gateways (AWS API Gateway)

Authentication & Authorization: OAuth 2.0, JWT, SAML, AWS IAM

Cloud & Infrastructure (AWS): AWS Lambda, AWS Step Functions, Amazon S3,

Amazon DynamoDB, AWS Glue, AWS EventBridge, AWS CloudFormation/CDK

Data Pipelines: AWS Glue, AWS Data Pipeline, Step Functions

Messaging & Streaming: AWS SNS, AWS SQS, Amazon Kinesis

Version Control: Git, GitHub/GitLab/Bitbucket

Containerization: Docker, Kubernetes (Amazon EKS is a plus)

Monitoring & Logging: AWS CloudWatch, AWS X-Ray

Security & Compliance: AWS IAM, AWS KMS, understanding of FERP

Wall Street, NY 10005 Hybrid work $65 - $85 an hour - Full-time, Contract, Job Types: Full-time, Contract

Pay: $65.00 - $85.00 per hour