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
