Applied AI engineer

Applied AI Engineer Position Overview We are seeking an Applied AI Engineer with a strong software engineering background to join our AI initiative team, focusing on building production LLM applications and implementing cutting-edge AI solutions. This role requires hands-on coding expertise across full-stack development with emphasis on LLM/RAG systems. Key Responsibilities Build production LLM applications using FastAPI/Spring Boot backends with React/Next.js frontends Implement and optimize RAG systems with vector databases (Pinecone, Weaviate, OpenSearch) Develop reusable LLM components (prompt engineering, chain orchestration, response streaming) Create REST/GraphQL APIs for AI services integration Deploy containerized AI applications on AWS (ECS/EKS, Lambda) Assess and evaluate AI tools, making strategic build vs. buy recommendations Implement caching, rate limiting, and guardrails for LLM APIs Required Technical Skills Programming Languages & Frameworks Python : FastAPI, Flask, Django (3+ years required) Java : Spring Boot, Spring Security, Spring Data JavaScript : React, Next.js, Node.js Strong API development and microservices architecture AI/ML Frameworks & Tools (Required) RAG Implementation : MUST HAVE - Production experience with RAG pipelines LangChain/LlamaIndex : Building AI applications and chains Vector Databases : Pinecone, Weaviate, OpenSearch Embedding Models : OpenAI, Cohere, Sentence Transformers Data Science:

Foundation knowledge Development Tools (Required) Cursor

OR

Windsurf : AI-powered development environments GitHub Copilot/CodeWhisperer : AI productivity tools AWS Cloud Platform (Required) AWS Bedrock : Managed foundation models Prompt Engineering : Advanced prompt design and optimization AI Guardrails : Safety and content filtering mechanisms Additional: Lambda, ECS/EKS, API Gateway, S3, DynamoDB Experience Requirements 3-5 years in

software engineering eCommerce experience

strongly preferred (product search, chatbots, personalization) Production web application development Agile/DevOps practices What You'll Work On eCommerce AI features: conversational commerce, semantic search, content generation API-first AI microservices following best practices POCs demonstrating AI capabilities and ROI Technical documentation and implementation guide