Applied AI engineerHSAD North America • Englewood Cliffs, NJ, United States
Applied AI engineer
HSAD North America • Englewood Cliffs, NJ, United States
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job_description.job_card.job_descriptionPython : 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 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 Cursor OR Windsurf : AI-powered development environments GitHub Copilot / CodeWhisperer : AI productivity tools 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 3-5 years in software engineering eCommerce experience strongly preferred (product search, chatbots, personalization) Production web application development Agile / DevOps practices 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
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
AI / ML Frameworks & Tools (Required)
Development Tools (Required)
AWS Cloud Platform (Required)
Experience Requirements
What You'll Work On
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Applied Ai Engineer • Englewood Cliffs, NJ, United States
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