Description

You will lead the architecture and delivery of applied AI solutions using Large and Small Language Models in a production environment.

Responsibilities

• Manage delivery for AI engineering initiatives, ensuring projects meet scope, timeline, and quality standards.
• Architect and develop Agentic AI applications leveraging LLMs and SMLs for automation and content generation.
• Lead and mentor AI engineers on architecture, design, and implementation best practices for distributed AI systems.
• Drive productionization, ensuring reliability, observability, and lifecycle management of deployed models.

Required Skills

• 7+ years of software or AI engineering experience, with 2+ years in a leadership or architecture role.
• Proven experience delivering LLM and SML-based applied AI systems into production.
• Expertise in Python, FastAPI, Azure Cloud, and containerized environments (Kubernetes).
• Demonstrated experience managing delivery for engineering teams or multi-stream technical projects.
• Strong foundation in distributed systems, microservices, and event-driven architectures.
• Experience with LangChain, LangGraph, vector databases, and RAG pipelines.
• Familiarity with Kafka and CI/CD practices.

Key Skills

Education

Bachelor's or Master's degrees