Gen AI Search Engineer

Design, develop, and deploy Gen AI-powered search features leveraging OpenAI models (e.g., GPT-3, GPT-4, embeddings) and Lucidworks Fusion. Integrate and fine-tune large language models (LLMs) with Fusion's search pipelines to enhance query understanding, semantic search, summarization, question answering, and content generation. Develop and implement strategies for indexing, retrieving, and ranking information optimized for Gen AI applications within the Fusion environment. Build robust and scalable APIs and microservices to connect Gen AI models with the Fusion platform. Collaborate with data scientists, search architects, and product managers to define requirements and deliver innovative search solutions. Experiment with different Gen AI techniques and evaluate their effectiveness in improving search relevance and user experience. Monitor and analyze the performance of Gen AI-enhanced search features, identifying areas for optimization and improvement. Stay up-to-date with the latest advancements in Generative AI, natural language processing (NLP), and search technologies. Contribute to the development of best practices and documentation for Gen AI integration within the search architecture. Troubleshoot and resolve technical issues related to Gen AI and Fusion integration Bachelor's or higher degree in Computer Science, Engineering, or a related field. Proven experience (typically 5+ years) in search engineering or a related software development 2+ years of Programming experience preferably using Python. Strong understanding of search engine principles, information retrieval, and relevance ranking. Hands-on experience working with Lucidworks Fusion, including pipeline development, query processing, and analytics. Significant experience working with OpenAI APIs and models (e.g., completions, embeddings, fine-tuning). Solid programming skills in languages such as Python and Java. Experience with NLP techniques and libraries (e.g., NLTK, spaCy, Transformers). Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Excellent problem-solving, analytical, and communication skills. Ability to work independently and collaboratively in a fast-paced environment. Experience with other enterprise search platforms (e.g., Elasticsearch, Solr). Knowledge of vector databases and similarity search techniques. Experience with MLOps practices for deploying and monitoring AI models. Contributions to open-source projects in the search or NLP domains. Familiarity with agile development methodologies. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. Salary range for the position: $99,000 - $156,000 per year. The successful candidate may be eligible for an annual discretionary incentive compensation award. The successful candidate may be eligible to participate in the relevant business unit's incentive compensation plan, which also may include a discretionary bonus component. Please visit mybenefits.morganstanley.com to learn more about our benefit offerings. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees. It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.