Job Description:
Responsibilities
Architect and scale multi-agent systems, LLM orchestrations, and retrieval-augmented generation (RAG) frameworks.
Build robust RESTful APIs and integrate AI microservices with enterprise data stores and vector databases.
Deploy, monitor, and optimize AI models on cloud platforms (AWS, Azure, or GCP) for latency, cost, and reliability.
Define technical standards, review system designs, and guide engineering best practices.
Create automated evaluation and testing pipelines to track model accuracy and prevent degradation.
Collaborate with product managers, data scientists, and security teams to align AI features with business needs.
Required Qualifications & Skills
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
4+ to 5+ years of hands-on software and AI/ML engineering experience, with proof of shipped production applications.
Strong programming proficiency in Python, Java, or Go.
Working knowledge of LLM orchestration tools (LangChain, LangGraph, LlamaIndex) and vector stores.
Experience with cloud containerization and infrastructure (Docker, Kubernetes, AWS/Azure/GCP).
Solid understanding of distributed system architecture and LLMOps/MLOps practices.
Industry:
Not For Profit
Category:
Human Services
Skills:
Communication