Design, develop, and deploy AI-driven features and services for the client’s platform.
Integrate LLMs (e.g., Anthropic Claude, OpenAI GPTs, Bedrock models) into production workflows.
Build and maintain backend services using Node.js and MongoDB.
Collaborate on full-stack development (Vue.js frontend) when needed.
Architect, containerize, and deploy applications using AWS (EC2, Fargate, Lambda, SQS, SES, S3, CloudFront) and Docker.
Implement data pipelines, web scraping solutions, and AI/data engineering workflows.
Optimize system performance, scalability, and reliability in a cloud-native environment.
Support ongoing AI experimentation and transition prototypes into production-ready Systems.

Requirements

3+ years of experience as an AI Engineer.
Strong experience in backend or full-stack development (Node.js, MongoDB required; Vue.js a plus).
Hands-on experience deploying applications on AWS (EC2, Fargate, Lambda, SQS, S3, etc.) with Docker.
Experience integrating and operationalizing LLMs (e.g., OpenAI, Anthropic, AWS Bedrock).
Proficiency in Python for AI/ML or data engineering tasks preferred.
Solid understanding of AI/ML fundamentals, NLP, and production ML workflows.
Experience with data engineering, web scraping, and building scalable data pipelines.
Ability to move from AI prototypes to secure, maintainable, production-grade systems.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI-driven featuresLLMsNode.jsMongoDBVue.jsAWSDockerPythondata engineeringweb scraping

Soft Skills

collaborationproblem-solvingadaptabilitycommunicationcreativity