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 you'll 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.

Machine Learning Engineer - Hybrid Remote

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