Software Engineer, AI/ML

Omnissa is the first AI-driven digital work platform, built to support flexible, secure, work-from anywhere experiences. As a Software Engineer, you will join the Globalization Engineering team to build AI-driven services and tools that power internationalization and localization across Omnissa's digital work platform.

Responsibilities:

• Design, build, and scale backend services in Python, Node.js, and TypeScript that support globalization, internationalization, and localization workflows
• Develop and integrate AI/ML and LLM-based solutions—including RAG/GraphRAG architectures, vector embeddings, and semantic retrieval—to improve translation and localization quality
• Build and maintain CI/CD pipelines, containerized services (Docker, Kubernetes), and RESTful APIs deployed on Azure, AWS, GCP, or similar cloud platforms
• Integrate LLM endpoints (Azure OpenAI, AWS, or equivalent) with enterprise systems using MCP and orchestration frameworks such as LangChain or LangGraph
• Work with SQL, NoSQL, and graph databases (e.g., Neo4j/Cypher) to support scalable, data-driven globalization solutions
• Collaborate cross-functionally with product, engineering, and localization stakeholders to advance Omnissa's globalization strategy

Requirements:

• Strong skills in Python, with hands-on experience using AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face
• Proficiency in Node.js and TypeScript (or comparable backend frameworks)
• Experience with Java or C# is a plus
• Proficiency with SQL and NoSQL databases
• Experience with Docker, Kubernetes, CI/CD, and RESTful APIs
• Experience building CI/CD pipelines using tools such as GitHub, Jenkins, or equivalent
• Knowledge of vector embeddings, RAG/GraphRAG architectures, and retrieval frameworks
• Experience with graph databases (Neo4j/Cypher or equivalent)
• Experience integrating LLM endpoints (Azure OpenAI, AWS, or equivalent)
• Experience integrating LLMs with enterprise systems using MCP
• Experience deploying scalable AI services on Azure, AWS, GCP, or similar tools
• Familiarity with LangChain, LangGraph, or similar LLM orchestration frameworks
• Bachelor's or Master's degree in Computer Science or a related field preferred, or equivalent combination of education and relevant professional experience
• Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions using vector search and semantic retrieval
• Experience building agentic AI systems using tools such as LangGraph, n8n, or Flowise
• Front-end development experience with React.js and HTML/CSS/JavaScript frameworks
• Experience with embedding models, vector databases, and semantic search technologies
• Knowledge of internationalization (i18n) standards and best practices is a nice to have