Job Title : LLM Engineer.

Job Type : Contract.

Location : Hybrid Bangalore, Pune or Delhi.

Job Summary :

Join our customer's dynamic team as an LLM Engineer, where youll leverage advanced language models and cutting-edge frameworks to build high-impact AI solutions.

As a core contributor, you will help architect, deploy, and optimize LLM-powered applications using modern tools and methodologies in a collaborative, agile environment.

Key Responsibilities :

- Design, develop, and deploy applications powered by large language models (LLMs) to solve real-world problems.

- Integrate and optimize LLM APIs with frameworks such as LangGraph and DSPy for enhanced tool orchestration.

- Implement and maintain vector databases (such as Qdrant, Milvus, or Pgvector) to support scalable data retrieval and storage operations.

- Collaborate effectively with team members using Azure DevOps, ensuring streamlined CI/CD pipelines and agile best practices.

- Work closely with cross-functional teams to understand requirements, deliver solutions, and contribute to architectural decisions.

- Troubleshoot, monitor, and enhance MCP server environments to ensure robust and reliable application performance.

- Continuously document solutions and communicate technical concepts clearly in both written and verbal formats.

Required Skills and Qualifications :

- Proven experience developing with large language models (LLMs) in production environments.

- Hands-on proficiency with LangGraph and DSPy for advanced language model application workflows.

- Strong knowledge of LLM API integration and practical tool use in AI/ML pipelines.

- Expertise in deploying and managing vector databases such as Qdrant, Milvus, or Pgvector.

- Familiarity with Azure DevOps and agile development processes for efficient project execution.

- Demonstrated skill in maintaining and optimizing MCP server environments.

- Exceptional written and verbal communication skills, with a passion for clear, effective information exchange.

Preferred Qualifications :

- Prior experience working in remote, distributed teams on AI-driven or SaaS products.

- Background in developing and deploying AI tools within enterprise-grade cloud ecosystems.

- Contributions to open-source LLM or AI infrastructure projects.