Artificial Intelligence Engineer - LLM

Description :

Role : AI Engineer - Python | LLM | LangChain | FastAPI

Location : Remote / Hybrid

Experience : 8 - 12 Years

Employment Type : Full-Time

About the Role :

We are looking for a highly skilled AI Engineer with deep expertise in Python-based AI development, strong experience in LLM-powered systems, and hands-on exposure to modern agent frameworks like LangChain and LangGraph.

The ideal candidate will have a strong backend engineering foundation and experience building scalable, production-grade AI applications using FastAPI.

This role involves designing and deploying enterprise-level LLM applications, developing agent-based workflows, and integrating AI systems with APIs, databases, and cloud services.

Key Responsibilities :

- Design, architect, and deploy LLM-powered applications using modern AI frameworks

- Develop robust prompting strategies and optimize LLM interactions

- Build and manage agent-based workflows using LangChain and LangGraph

- Implement orchestration logic for complex multi-step AI pipelines

- Develop scalable, secure, and high-performance backend services using FastAPI

- Integrate AI systems with REST APIs, third-party services, databases, and enterprise tools

- Work with vector databases for semantic search and RAG pipelines

- Optimize model performance, latency, and cost efficiency

- Conduct model evaluation, testing, benchmarking, and monitoring

- Collaborate with product managers, data scientists, and DevOps teams to deliver production-ready AI solutions

- Ensure best practices in system design, scalability, observability, and security

Required Skills & Qualifications :

- 8 - 12 years of hands-on experience in software development with at least 3 - 5 years in AI/LLM-based systems

- Strong proficiency in Python for backend development and AI workflows

- Hands-on experience building APIs using FastAPI

- Solid understanding of LLM architecture and integration (OpenAI, Anthropic, open-source LLMs, etc.)

- Strong experience with LangChain (agents, tools, memory, chains, RAG)

- Experience with LangGraph for