AI Application Software Developer

We are seeking an innovative and highly skilled AI Application Engineer to be a part of our team and contribute to the development of cutting-edge enterprise-scale, public-facing AI applications. In this role, you will have the exciting opportunity to shape the future of autonomous agent-based systems, with a focus on performance, scalability, and utilizing advanced technologies such as LLMs, embedding techniques, and agentic frameworks. As an AI Application Engineer, your responsibilities will include designing and implementing solutions that not only meet user expectations but also optimize system performance. This position requires a blend of technical expertise, creativity, and a dedication to achieving excellence in application engineering. You will be expected to: - Design, develop, and deploy enterprise-scale, public-facing AI applications. - Implement advanced Retrieval Augmented Generation (RAG) architectures, including hybrid search and multi-vector retrieval. - Build and optimize systems for token usage, response caching, and performance tuning. - Develop and maintain autonomous agent frameworks using LangGraph or a similar framework. - Drive innovation in areas such as embedding techniques, contextual compression, and multi-agent systems. - Collaborate with cross-functional teams, including product managers, designers, and DevOps, to deliver robust and user-centric solutions. - Troubleshoot complex technical challenges and provide mentorship to junior developers. - Stay informed about the latest advancements in LLMs, agentic frameworks, and AI-driven application development. Minimum Qualifications: - 3 years of hands-on experience developing production-grade LLM applications. - 3 to 5 years of overall software development experience. - Minimum 1 year of experience in autonomous agent development using the LangGraph framework or a similar framework. Must-Have Skills: 1. Production-Grade LLM Development: Demonstrated experience in developing and deploying large language model applications. 2. Autonomous Agent Development: Practical experience with frameworks like LangGraph for constructing autonomous agents. 3. Advanced RAG Architectures: Proficiency in hybrid search, multi-vector retrieval, and contextual compression. 4. Prompt Engineering and Vector Search Optimization: Skill in crafting effective prompts and optimizing vector searches. 5. Performance Tuning and Token Optimization: Strong understanding of response caching and techniques for optimizing token usage. Nice-to-Have Skills: 1. Scalable Architectures: Familiarity with Kubernetes, Docker, and cloud platforms, particularly Azure. 2. NoSQL Databases: Knowledge of MongoDB and Elasticsearch. 3. API-Driven Development: Experience in building and maintaining APIs. 4. CI/CD Pipelines and Agile Methodologies: Proficiency with continuous integration/continuous deployment pipelines and Agile practices. 5. Analytical and Problem-Solving Skills: Strong analytical abilities and attention to detail will be beneficial in this role.,