QUALIFICATIONS
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Experience with OpenSearch/Elastic Search, including knowledge of text analyzers, cluster management, Elasticsearch query DSL, aggregations, highlighting, percolation, and system scaling
- Ability to design indexing processes for large data volumes
- Experience in deploying web applications, ingestion and search pipelines, and microservices in production cloud environments within the software industry
- Proficiency in programming with Java Spring Boot Microservices
- Capability to troubleshoot issues independently
- Knowledge of Python programming is advantageous
- Understanding of semantic search and vector databases
- Familiarity with Solr is beneficial
- Ability to translate business requirements into technical solutions
WHO YOU'LL WORK WITH
You will be part of McKinsey Technology and Digital group addresses the firm's internal software development needs.
You will equip McKinsey’s business thought leaders with the tools and knowledge necessary for their global client engagements. Your development teams are small and flexible, utilizing agile methodologies to swiftly deliver the required solutions to your user community. You will be involved in integrating the latest open-source technologies with traditional Enterprise software products.
WHAT YOU'LL DO
As a Search Engineer, you will be responsible for designing, developing, and optimizing search functionality to enhance the relevance, efficiency, and scalability of search experiences. In this role, you will be working on search algorithms, indexing, ranking, and retrieval systems additionally leveraging Generative AI to deliver accurate and meaningful results for users.
As a Search System Development, you will design and implement search architectures, including indexing, ranking, and query parsing components. You will build and optimize search pipelines to support real-time and batch processing.
As a Algorithm Optimization , you will develop and fine-tune search algorithms to improve relevance and accuracy. You will be involved in implementing machine learning models and natural language processing (NLP) techniques to enhance query understanding and result ranking.
