Applied AI engineer

HSAD North America

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

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Need Help?

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