À propos de ce poste Sr Software Engineer chez GE Vernova
GE Vernova · Sur site · Bengaluru
Job Description Summary
Responsible for programing a component, feature and or feature set. Works independently and contributes to the immediate team and to other teams across business. You will also contribute to design discussions.Job Description
Roles and Responsibilities
- Build the AI Context Layer: Develop and maintain backend services and data pipelines that supply relevant business context, metadata, and constraints to LLM applications.
- Work with Semantic Models & Ontologies: Help implement, update, and query domain ontologies and taxonomies using standards like RDF, OWL, or SPARQL under the guidance of senior architects.
- Knowledge Graph Integration: Write code to interact with graph databases (e.g., Neo4j, AWS Neptune) to support semantic search and relationship mapping.
- Enhance Search & RAG Pipelines: Help build and optimize hybrid retrieval systems combining vector search (semantic similarity) with structured graph data for better LLM grounding.
- Data Pipelines: Write robust data ingestion and processing scripts to extract entities and relationships from various enterprise data sources.
- Collaboration: Partner with ML engineers, data scientists, and backend developers to integrate semantic components into production AI products.
- Code Quality: Write clean, testable, and well-documented code following best software engineering practices.
- Required Qualifications & Skills
- Experience: 4–6 years of software development experience, with at least 1–2 years working on data-heavy applications, NLP, vector search, or semantic/graph technologies.
- Programming: Strong backend development skills in Python (preferred for AI workflows) and/or Java/TypeScript.
- Databases & Storage: Experience working with relational databases and at least some exposure to NoSQL, vector databases (e.g., Pinecone, Milvus, Qdrant), or graph databases (e.g., Neo4j).
- Foundational Knowledge of Semantics/AI: Familiarity with concepts like knowledge graphs, vector embeddings, prompt engineering, or semantic web standards (RDF/OWL). We don't expect an ontology expert, but you should be eager to learn and work with them.
- API Development: Experience building and consuming RESTful APIs and microservices.
Education: Bachelor’s degree in computer science, software engineering, or a related technical field (or equivalent practical experience).
Additional Information
Relocation Assistance Provided: Yes
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