Summary

We are seeking a Mid-Level AI Engineer to join our team and contribute to the design, development, and deployment of modern AI-powered applications. The ideal candidate will have strong expertise in TypeScript/JavaScript, AWS Serverless architecture, and experience building and operating production-grade Generative AI applications. This role will focus on developing scalable backend services, integrating Large Language Models (LLMs), designing AI-powered workflows, evaluating model performance, and delivering reliable cloud-native solutions.

Responsibilities

• Design, develop, and maintain scalable backend services using TypeScript/JavaScript
• Build and operate cloud-native applications on AWS Serverless architecture using:
  • API Gateway
  • Lambda
  • DynamoDB
  • VPC
• Design and implement REST APIs and event-driven architectures
• Build and deploy production-grade Generative AI applications
• Develop RAG-based solutions using vector databases, embeddings, and modern LLM frameworks
• Engineer effective prompts and AI workflows to optimize application performance
• Conduct LLM evaluations, benchmarking, and performance analysis
• Implement AI observability, monitoring, and quality evaluation mechanisms
• Work with WebSocket-based real-time communication systems
• Build robust automated testing frameworks including:
  • Unit Testing
  • Integration Testing
• Implement and maintain CI/CD pipelines and deployment workflows
• Collaborate with Product, Engineering, and AI teams to deliver AI-powered features
• Troubleshoot, debug, and optimize application performance and reliability
• Contribute to architecture decisions and engineering best practices

Required Qualifications

• 3–6 years of professional software engineering experience
• Strong expertise in TypeScript/JavaScript
• Hands-on experience with AWS Serverless services:
  • API Gateway
  • Lambda
  • DynamoDB
  • VPC Networking
• Experience designing and building distributed backend systems
• Strong understanding of REST APIs, microservices, and event-driven architectures
• Experience with WebSockets and real-time communication systems
• Strong experience with Unit Testing and Integration Testing
• Experience building and supporting production-grade GenAI applications
• Experience working with LLMs such as:
  • OpenAI
  • Anthropic
  • Gemini
  • Open-source LLMs
• Experience with prompt engineering and prompt optimization techniques
• Experience conducting LLM evaluations and measuring model performance
• Familiarity with:
  • LangChain
  • LangGraph
  • LlamaIndex
  • Semantic Kernel
• Experience with vector databases, embeddings, and RAG architectures
• Strong software engineering fundamentals, design patterns, and system design skills
• Excellent problem-solving and communication skills