> Markdown version of [/jobs/ext/1891774-software-engineer-ai-ml](https://www.wearedevelopers.com/jobs/ext/1891774-software-engineer-ai-ml). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, AI/ML - **Company:** Omnissa, LLC - **Location:** Atlanta, GA, United States - **Salary:** $102,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Continuous Integration, Github, Graph Database, Python (Programming Language), Neo4j, Node.Js, NoSQL, Tensorflow, Search Technologies, SQL Databases, Systems Integration, TypeScript, Google Cloud, Enterprise Software Applications, Pytorch, ReactJS, Large Language Models, Generative AI, Backend, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Data Analytics, Nintex, Front End Software Development, Restful APIs, Docker, Jenkins - **Published:** August 1, 2026 - **Apply:** https://www.jofdav.com/jobs/59055301-software-engineer-ai-ml ## About the Role * 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, * 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, Education: Bachelor's or Master's degree in Computer Science or a related field preferred, or equivalent combination of education and relevant professional experience. ## Description 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. ## Related Videos - [Accelerating GenAI Development: Harnessing Astra DB Vector Store and Langflow for LLM-Powered Apps](https://www.wearedevelopers.com/videos/966-accelerating-genai-development-harnessing-astra-db-vector-store-and-langflow-for-llm-powered-apps) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Semantic AI: Why Embeddings Might Matter More Than LLMs](https://www.wearedevelopers.com/videos/1460-semantic-ai-why-embeddings-might-matter-more-than-llms) - [Cyber Sleuth: Finding Hidden Connections in Cyber Data](https://www.wearedevelopers.com/videos/893-cyber-sleuth-finding-hidden-connections-in-cyber-data) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)