Software Engineer - LLM Models

About the Role :

We are seeking a highly skilled and motivated AI Software Engineer to join our advanced AI development team.

In this role, you will play a crucial part in building, designing, and deploying enterprise-grade AI-driven applications using cutting-edge technologies like LangChain, LangGraph, and Azure OpenAI.

You will be responsible for developing full-stack solutions that integrate large language models (LLMs), implementing secure and scalable cloud-native systems, and contributing to the overall architecture and performance optimization of the platform.

This role demands deep technical expertise in backend and frontend development, strong problem-solving abilities, and a passion for AI-driven innovation.

Key Responsibilities :

- Architect and implement full-stack solutions using Python (FastAPI) for backend and React + TypeScript for frontend.

- Build and integrate LLM-based services and autonomous AI agents using frameworks like LangChain and LangGraph.

- Design and implement intelligent agent workflows using Azure OpenAI or similar APIs (OpenAI, Anthropic, Cohere).

- Fine-tune prompt engineering techniques to improve the performance and contextuality of LLM interactions.

- Optimize agent behavior and interaction flows based on application usage data and business logic.

- Deploy, monitor, and manage applications on AWS and Azure using services such as : Azure DevOps, Azure Active Directory, AWS EC2/ECS, Secrets Manager, IAM

- Implement continuous integration and delivery (CI/CD) pipelines via GitHub Actions, Azure DevOps, or similar tools.

- Ensure high availability, performance, and security of cloud-native systems.

- Design and manage NoSQL databases including MongoDB (Motor/Beanie ODM) and Redis for real-time data access and caching.

- Optimize data retrieval, search, and storage for LLM applications using vector databases and advanced caching strategies.

- Implement secure authentication and authorization systems using OAuth2, SAML, JWT, and Azure AD.

- Ensure proper audit logging, access control, and data compliance across deployed applications.

- Collaborate with product managers, designers, and QA teams to ensure seamless integration of AI features.

- Document solution architecture, conduct root cause analysis (RCA), and prepare technical documentation for deployments and upgrades.

- Mentor junior developers and contribute to the continuous improvement of engineering practices.