
LLM Engineer
2 weeks ago
Job Title: LLM Engineer
Location: Bangalore; Pune; Delhi (Hybrid – 3 days Office)
Experience : 4+ years
Client : Pranatree
Employment Type: Contract
About the Role
We are looking for a highly skilled LLM Engineer to design, develop, and optimize Large Language Model (LLM)-powered applications. This role requires deep expertise in LLM APIs, AI tool integrations, and vector database technologies. You will work with cutting-edge frameworks such as Lang Graph and DSPy, build tool-using AI systems, and leverage modern orchestration techniques to deliver intelligent, scalable, and high performance solutions.
Key Responsibilities
• 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. Required Skills & Qualifications
• 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.
Good to Have
• 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).
Why Join Us?
• Work on cutting-edge AI and LLM engineering projects.
• Collaborate with top-tier AI engineers in a hybrid, innovation-driven environment.
• Build solutions that leverage the latest in tool-use AI, vector search, and orchestration frameworks.
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