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
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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
Preferred Qualifications
Experience with AI agent frameworks and agentic workflows
Experience with AI evaluation frameworks such as LangSmith, Ragas, DeepEval, or equivalent
Familiarity with AI observability and monitoring platforms
Experience optimizing LLM cost, latency, and reliability
Exposure to multi-agent systems and advanced GenAI architectures
Ideal Candidate Profile
We are looking for engineers who have already built and deployed GenAI solutions into production and can contribute immediately within our TypeScript-based AWS Serverless ecosystem. Candidates with hands-on experience in LLM evaluations, prompt engineering, RAG architectures, WebSockets, and automated testing will be highly preferred.
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