What are the responsibilities and job description for the LLM Engineer position at Virtual Connect Solutions?
- Design and develop LLM-powered applications integrating APIs such as Open AI, Claude, Gemini,etc.
- Build AI workflows using Lang Graph, DSPy, and tool-use frameworks.
- Implement MCP server integrations to extend LLM capabilities.
- Work with vector databases such as Qdrant, Milvus, or Pgvector for semantic search and retrieval. Optimize prompt engineering, model orchestration, and tool chaining for performance and accuracy.
- Collaborate with cross-functional teams to translate requirements into AI-enabled solutions.
- Ensure solutions adhere to best practices in security, scalability, and maintainability.
- Use Azure DevOps for code management, CI/CD pipelines, and deployment.
- Participate in Agile ceremonies, sprint planning, and delivery reviews.
- Bachelor’s or master’s degree in computer science, AI/ML, Engineering, or related field.
- 4 years of experience in software development, with 2 years in LLM/AI application development. Strong hands-on experience with LLM APIs (Open AI, Claude, Gemini, etc.).
- Experience with Lang Graph, DSPy, and tool-use patterns in AI systems.
- Knowledge of MCP server integration and usage.
- Expertise in vector databases (Qdrant, Milvus, Pgvector).
- Familiarity with Azure DevOps and Agile delivery methodologies.
- Experience with RAG (Retrieval-Augmented Generation) pipelines.
- Knowledge of MLOps practices and AI model deployment.
- Familiarity with multi-cloud environments (Azure, AWS, GCP).
- Exposure to containerization (Docker, Kubernetes).
Salary : $60 - $70