LLM Integration Engineer/Remote

Job Description- LLM Integration Engineer

About the Role

We are seeking an LLM Integration Engineer to develop and integrate Large Language Model (LLM) solutions into applications, workflows, and enterprise systems. The ideal candidate should have experience working with AI APIs, backend systems, and orchestration frameworks to build scalable and reliable AI-powered products.

Key Responsibilities

• Integrate LLMs such as OpenAI, Claude, Gemini, or open-source models into applications.
• Build AI-powered APIs, workflows, and backend services using Python.
• Develop prompt engineering, tool-calling, and agent workflows.
• Integrate AI systems with databases, APIs, and third-party platforms.
• Optimize model responses, latency, and operational costs.
• Implement RAG pipelines, vector search, and context management systems.
• Monitor, debug, and maintain production AI integrations.
• Collaborate with product, engineering, and AI teams to deliver features.

Required Skills

• Strong proficiency in Python.
• Experience integrating LLM APIs and AI services.
• Knowledge of REST APIs and backend development.
• Familiarity with LangChain, LangGraph, CrewAI, or similar frameworks.
• Understanding of prompt engineering and AI workflow design.
• Experience with databases such as PostgreSQL, MongoDB, or Redis.
• Strong debugging and analytical skills.

Preferred Qualifications

• Experience with vector databases and RAG architectures.
• Familiarity with Docker, Kubernetes, and cloud platforms (AWS/Google Cloud Platform/Azure).
• Experience with FastAPI, Flask, or microservices architectures.
• Knowledge of observability, monitoring, and AI evaluation tools.
• Exposure to CI/CD and deployment automation.

Nice to Have

• Experience building multi-agent AI systems.
• Understanding of AI governance, safety, and guardrails.
• Familiarity with asynchronous programming and distributed systems.
• Experience with MCP servers or enterprise AI integrations.

Tools & Technologies

Python, OpenAI APIs, LangChain, LangGraph, FastAPI, PostgreSQL, Redis, Docker, Kubernetes, AWS/Google Cloud Platform, Vector Databases, Git.