Overview
The AI Engineer - LLM & Agentic Systems will play a pivotal role in designing and developing advanced AI agents and workflows that leverage large language models (LLMs) to address complex business challenges. Working in a hybrid environment, the contractor will collaborate with diverse engineering teams to ensure the integration of AI technologies within core products and workflows, focusing on delivering scalable and reliable solutions that enhance usability and performance.
Responsibilities
- Design and build AI agents and workflows utilizing LLMs, RAG, and multi-step reasoning.
- Own the end-to-end delivery from initial exploration to production deployment and iteration.
- Develop systems using MCP-style architectures with frameworks like FastMCP and LangChain.
- Integrate AI solutions into products, APIs, and business processes focusing on performance metrics.
- Collaborate with engineering teams to enhance system observability and maintainability.
- Ensure production-grade code quality and adherence to system design principles.
- Utilize cloud platforms (AWS, GCP, Azure) for system deployment and management.
- Mentor junior engineers and contribute to team knowledge sharing.
Requirements
- Proven experience with production-grade LLM-powered systems and AI agents.
- Strong proficiency in Python and machine learning principles.
- Hands-on experience with RAG systems and tool orchestration.
- Familiarity with cloud services (AWS, GCP, Azure) and modern engineering practices.
- Solid understanding of system design principles and trade-offs in LLMs.
- Possession of a Masters or higher in a relevant scientific or technical field.
- Experience in SaaS or B2B AI product development is desirable.
- Demonstrated ability to take ownership of projects and mentor others in the team.