L2 Engineer - Coach

<h3><strong>L2 Engineer – GenAI Focused</strong></h3> <p><strong>Location:</strong> Pune</p> <h3><strong>Summary</strong></h3> <p>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 <strong>TypeScript/JavaScript</strong>, <strong>AWS Serverless architecture</strong>, and experience building and operating <strong>production-grade Generative AI applications</strong>.</p> <p>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.</p> <h3><strong>

Responsibilities</strong></h3> <ul> <li>Design, develop, and maintain scalable backend services using <strong>TypeScript/JavaScript</strong></li> <li>Build and operate cloud-native applications on AWS Serverless architecture using:</li> <ul> <li>API Gateway</li> <li>Lambda</li> <li>DynamoDB</li> <li>VPC</li> </ul> <li>Design and implement REST APIs and event-driven architectures</li> <li>Build and deploy production-grade Generative AI applications</li> <li>Develop RAG-based solutions using vector databases, embeddings, and modern LLM frameworks</li> <li>Engineer effective prompts and AI workflows to optimize application performance</li> <li>Conduct LLM evaluations, benchmarking, and performance analysis</li> <li>Implement AI observability, monitoring, and quality evaluation mechanisms</li> <li>Work with WebSocket-based real-time communication systems</li> <li>Build robust automated testing frameworks including:</li> <ul> <li>Unit Testing</li> <li>Integration Testing</li> </ul> <li>Implement and maintain CI/CD pipelines and deployment workflows</li> <li>Collaborate with Product, Engineering, and AI teams to deliver AI-powered features</li> <li>Troubleshoot, debug, and optimize application performance and reliability</li> <li>Contribute to architecture decisions and engineering best practices</li> </ul> <h3><strong>Required

Qualifications</strong></h3> <ul> <li>3–6 years of professional software engineering experience</li> <li>Strong expertise in <strong>TypeScript/JavaScript</strong></li> <li>Hands-on experience with AWS Serverless services:</li> <ul> <li>API Gateway</li> <li>Lambda</li> <li>DynamoDB</li> <li>VPC Networking</li> </ul> <li>Experience designing and building distributed backend systems</li> <li>Strong understanding of REST APIs, microservices, and event-driven architectures</li> <li>Experience with WebSockets and real-time communication systems</li> <li>Strong experience with Unit Testing and Integration Testing</li> <li>Experience building and supporting production-grade GenAI applications</li> <li>Experience working with LLMs such as:</li> <ul> <li>OpenAI</li> <li>Anthropic</li> <li>Gemini</li> <li>Open-source LLMs</li> </ul> <li>Experience with prompt engineering and prompt optimization techniques</li> <li>Experience conducting LLM evaluations and measuring model performance</li> <li>Familiarity with:</li> <ul> <li>LangChain</li> <li>LangGraph</li> <li>LlamaIndex</li> <li>Semantic Kernel</li> </ul> <li>Experience with vector databases, embeddings, and RAG architectures</li> <li>Strong software engineering fundamentals, design patterns, and system design skills</li> <li>Excellent problem-solving and communication skills</li> </ul> <h3><strong>Preferred

Qualifications</strong></h3> <ul> <li>Experience with AI agent frameworks and agentic workflows</li> <li>Experience with AI evaluation frameworks such as LangSmith, Ragas, DeepEval, or equivalent</li> <li>Familiarity with AI observability and monitoring platforms</li> <li>Experience optimizing LLM cost, latency, and reliability</li> <li>Exposure to multi-agent systems and advanced GenAI architectures</li> </ul> <h3><strong>Ideal Candidate Profile</strong></h3> <p>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.</p> <p> </p>