3 Llm Development Jobs

Title: Agentic AI and Domain-Specific LLM Developer We are seeking talented and passionate developers with experience in developing customized solutions based on the NVIDIA Morpheus Cyber AI framework to join our team. In this role, you will be instrumental in the development of a state-of-the-art Grid Cybersecurity software platform designed to safeguard electric sector critical infrastructure from emerging cyber threats. Your new role will be challenging and future-oriented: Design, develop, and implement cybersecurity solutions using NVIDIA Morpheus Cyber AI framework, NVIDIA AgentIQ toolkit, NVIDIA Blue Field, Domain-Specific LLM, Open API, and OpenUSD. Collaborate with cross-functional teams to integrate AI-driven security features into the Grid Cybersecurity platform. Analyze and process large datasets to identify and mitigate potential published and zero-day OT/ICS vulnerabilities. Develop and maintain robust, scalable, and secure software CI/CD processes and have experience with DevSecOps software composition analysis tools. Troubleshoot, debug, and optimize existing software for improved performance and security. Stay up to date with the latest advancements in AI and cybersecurity to ensure our platform remains at the forefront of innovation. We dont need superheroes, just super minds: Bachelor masters degree in Artificial Intelligence, OT/ICS Cybersecurity, Computer Science, Embedded Device Engineering, or a related field. Proven experience with NVIDIA Morpheus Cyber AI framework and comparable AI frameworks. Experience with operational technology (OT)/industrial control systems (ICS) critical infrastructure cybersecurity technologies. Strong programming skills in Python. Additional languages such as C++ or Java is a plus. Commercial product experience with AI, machine learning, and customizing common AI frameworks for specific use cases. Strong experience with DevOps, DevSecOps, AIOps/AI Governance, and MLOps. Stay up to date on new developments in AI for Cybersecurity. Experience presenting at technical conferences is a plus. Experience with AI trust documentation projects. Ability to work collaboratively in a fast-paced, dynamic environment. Excellent innovation, problem-solving, and communication skills. Familiarity with project management systems, including Jira or Trello. Familiarity with Software Bill of Materials (SBOM) for vulnerability management. Experience with grid computing and large-scale distributed data processing. Knowledge of private cloud platforms such as AWS, Azure, or Google Cloud. Understanding of networking protocols and security measures. Experience with digital twins for cybersecurity.

Senior Backend Engineer Role & Responsibilities Design and implement scalable backend systems using Python (FastAPI preferred) and RESTful API services. Integrate and operationalize LLMs (e.g., OpenAI, Azure OpenAI, Hugging Face models) into end-user applications. Develop and maintain pipelines for prompt orchestration, embeddings, and retrieval- augmented generation (RAG). Work with vector databases (e.g., FAISS, Pinecone, Azure Cognitive Search) for context- aware LLM responses. Ensure robustness, performance, and security of API endpoints and backend services. Collaborate with front-end developers, ML engineers, and client stakeholders to deliver high-quality features. Participate in architecture design discussions and contribute to code reviews and technical documentation. Take end-to-end ownership of features and independently manage tasks and delivery timelines. Support knowledge transfer from client-side experts and progressively reduce dependency on them. Must-Have Skills: 6+ years of strong hands-on experience in Python backend development, with a focus on RESTful APIs. Experience in integrating LLMs via APIs (OpenAI, Azure OpenAI, Hugging Face Transformers). Strong understanding of RAG patterns, prompt engineering, and context injection for GenAI applications. Experience working with vector databases or semantic search frameworks. Experience with cloud platforms, preferably Azure (Azure Functions, Cognitive Services, etc.). Proficiency in problem-solving, debugging, and performance tuning. Strong communication skills; able to articulate technical ideas and challenges clearly. Ability to work independently and mentor junior engineers when needed. Good-to-Have Skills: Experience with LangChain, LLM orchestration frameworks, or prompt tuning. Experience in containerization (Docker, Kubernetes). Familiarity with CI/CD pipelines and version control (Git). Prior exposure to enterprise AI solutions or chatbot frameworks

We seek a Senior AI Scientist with strong ML fundamentals and data engineering expertise to lead the development of scalable AI/LLM solutions. You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices. Key Responsibilities 1. AI/LLM Development: o Fine-tune and optimize LLMs (e.g., GPT, Llama) and traditional ML models for production. o Implement retrieval-augmented generation (RAG), vector databases, and orchestration tools (e.g., LangChain). 2. Data Engineering: o Build scalable data pipelines for unstructured/text data (e.g., Spark, Kafka, Airflow). o Optimize storage/retrieval for embeddings (e.g., pgvector, Pinecone). 3. MLOps & Deployment: o Containerize models (Docker) and deploy on cloud (AWS/Azure/GCP) using Kubernetes. o Design CI/CD pipelines for LLM workflows (experiment tracking, monitoring). 4. Collaboration: o Work with DevOps to optimize latency/cost trade-offs for LLM APIs. o Mentor junior team members on ML engineering best practices. Required Skills & Qualifications Education: MS/PhD in CS/AI/Data Science (or equivalent experience). Experience: 6+ years in ML + data engineering, with 2+ years in LLM/GenAI projects.