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Showpad is seeking a Mid-Level AI Engineer to join their 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 hands-on experience building and operating production-grade Generative AI applications.
Key Responsibilities:
- Design, develop, and maintain scalable backend services using TypeScript/JavaScript
- Build and operate cloud-native applications on AWS Serverless architecture (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 (unit and 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 (OpenAI, Anthropic, Gemini, open-source models)
- 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
Preferred Qualifications:
- Experience with AI agent frameworks and agentic workflows
- Experience with AI evaluation frameworks (LangSmith, Ragas, DeepEval)
- Familiarity with AI observability and monitoring platforms
- Experience optimizing LLM cost, latency, and reliability
- Exposure to multi-agent systems and advanced GenAI architectures
