AI Solutions Engineer

Job Title: AI Solutions Engineer

Position Summary:

The AI Solutions Engineer is a hands-on technical role responsible for designing, developing, and deploying advanced AI agents and data solutions, with a strong emphasis on integration with data lake environments. This position requires deep expertise in building robust, stateful AI applications using Python, LangChain, and LangGraph, managing data transformation with DBT, and deploying scalable solutions using Docker, MCP Servers, and NGINX or similar technologies.

The ideal candidate will play a critical role in the development, configuration, and performance optimization of AI agents and data pipelines, ensuring seamless integration with Data Lakes, Delta Lakes, or Lakehouse architectures via Model Context Protocol (MCP). Strong collaboration, problem-solving, and communication skills are essential.

Key Responsibilities:

• Design, build, and optimize complex, stateful AI agents and multi-actor applications using Python, LangChain, and LangGraph.
• Develop and manage interfaces with MCP servers to enable seamless communication between AI models and external systems (e.g., databases, APIs, file systems).
• Build and maintain scalable data ingestion and transformation pipelines using DBT to ensure data quality, freshness, and accessibility for AI models.
• Utilize Docker and Docker Compose for containerization and orchestration of AI applications and MCP servers, ensuring reproducible and scalable deployments.
• Configure and manage web servers (e.g., NGINX) to route traffic, secure connections, and optimize performance and latency of deployed AI services.
• Collaborate with frontend developers to integrate AI backend logic into user-facing interfaces, potentially using platforms like LibreChat.
• Implement testing frameworks for data quality and AI model behavior; debug and optimize applications for performance, security, and scalability.
• Work closely with data scientists, analysts, and product managers to define requirements, deliver technical solutions, and maintain clear documentation of architectures and processes.

Required Skills & Qualifications:

• Strong proficiency in Python and related libraries for AI/ML and backend development (e.g., FastAPI, Pandas).
• Hands-on experience with LangChain and LangGraph for building LLM-powered applications and managing agent workflows.
• Proven experience with DBT for data modeling, testing, and documentation within a modern data stack.
• In-depth knowledge of Docker, Docker Compose, and CI/CD pipelines; familiarity with Kubernetes fundamentals is a plus.
• Experience configuring and managing NGINX for reverse proxy, load balancing, and secure communication (SSL/TLS).
• Understanding of Model Context Protocol (MCP) and experience integrating MCP clients and servers.
• Strong analytical and troubleshooting skills for complex, distributed systems.

Education:

Bachelors degree in Computer Science, Engineering, or a related technical field (preferred).