LLM Engineer

2 weeks ago


Bharatpur, Rajasthan, India NTek Software Solutions Full time

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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