AI Use-Case Development Platform
Budget: €250 – €750 EUR
We're ready to add production-grade AI to our web platform and need a developer who has experience taking AI products from concept to live deployment.
Our platform uses React, Node/Express, PostgreSQL, and AWS. We are looking to implement AI capabilities
The engagement will begin with an evaluation of our current architecture and data assets, followed by recommendations for the highest-impact AI features. Once priorities are agreed upon, you'll design, develop, deploy, and integrate the AI services into our existing platform.
Key Deliverables
Technical design covering model selection, architecture, data requirements, and integration strategy
AI services and APIs deployed as microservices or serverless functions on AWS (ECS/Fargate/Lambda)
Model training, fine-tuning, evaluation, and monitoring
REST APIs with Swagger/OpenAPI documentation and automated tests
Infrastructure as Code (Terraform or CloudFormation)
CI/CD integration and deployment automation
Knowledge transfer and handoff documentation
Ideal Experience
Production deployment of LLMs, recommendation systems, predictive analytics, or talent marketplace solutions
NLP for resume parsing, skills extraction, matching, and assessments
Predictive modeling and forecasting
AWS AI/ML infrastructure
Strong focus on scalability, latency, security, and cost optimization
We're looking for someone who can clearly explain trade-offs, validate outcomes with measurable metrics, and own the project end-to-end from design through production deployment.
Our platform uses React, Node/Express, PostgreSQL, and AWS. We are looking to implement AI capabilities
The engagement will begin with an evaluation of our current architecture and data assets, followed by recommendations for the highest-impact AI features. Once priorities are agreed upon, you'll design, develop, deploy, and integrate the AI services into our existing platform.
Key Deliverables
Technical design covering model selection, architecture, data requirements, and integration strategy
AI services and APIs deployed as microservices or serverless functions on AWS (ECS/Fargate/Lambda)
Model training, fine-tuning, evaluation, and monitoring
REST APIs with Swagger/OpenAPI documentation and automated tests
Infrastructure as Code (Terraform or CloudFormation)
CI/CD integration and deployment automation
Knowledge transfer and handoff documentation
Ideal Experience
Production deployment of LLMs, recommendation systems, predictive analytics, or talent marketplace solutions
NLP for resume parsing, skills extraction, matching, and assessments
Predictive modeling and forecasting
AWS AI/ML infrastructure
Strong focus on scalability, latency, security, and cost optimization
We're looking for someone who can clearly explain trade-offs, validate outcomes with measurable metrics, and own the project end-to-end from design through production deployment.