Job Description:What is the opportunity?:As a Software Engineer, you will join our Globalization Engineering team, building the AI-driven services, tools, and platforms that power internationalization (i18n) and localization across Omnissa's digital work platform. You will design and scale backend systems, integrate large language model (LLM) capabilities, and help embed globalization best practices into our engineering workflows. Here is a breakdown:
- 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.
What will you bring to Omnissa?- 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
Preferred Qualifications:- 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
Location: USA
Location Type: Remote or Hybrid
Travel Expectations: None
Education: Bachelor's or Master's degree in Computer Science or a related field preferred, or equivalent combination of education and relevant professional experience.
Compensation: The typical base salary for this role is between USD $102,000 - $160,000 per year and it may be eligible for participation in a corporate bonus program. Actual compensation offer may vary from posted hiring range based upon geographic location, work experience, education, skill level, or other relevant factors. In addition to competitive compensation, Omnissa offers a variety of benefits such as employee ownership, health insurance, 401k with matching contributions, disability insurance, paid-time off, growth opportunities, and more.
