Director of Engineering (AI)

TL;DR

Director of Engineering (AI): Leading the design and development of enterprise-grade agentic AI solutions and frameworks for Evergreen.AI with an accent on scalability, production readiness, and multi-agent orchestration. Focus on building high-performing global engineering teams and ensuring operational excellence for Fortune 500 clients.

Location: On-site in Atlanta, Georgia

Company

hirify.global is building the Evergreen.AI foundry to deliver secure, resilient, and compliant AI solutions for Fortune 500 clients.

What you will do

• Build and lead high-performing engineering teams across regions, establishing career frameworks and mentorship programs.
• Define agentic AI architecture, including multi-agent orchestration, LLM knowledge management, and enterprise integration patterns.
• Drive production readiness by implementing runbooks, observability, SLAs, and resiliency patterns for multi-region deployments.
• Implement secure SDLC, CI/CD, LLMOps/MLOps, and DevSecOps practices adhering to SOC 2, ISO 27001, HIPAA, and GDPR standards.
• Own the end-to-end ML lifecycle, including data ingestion, model training, serving, and evaluation with production-grade MLOps.
• Engage directly with executive stakeholders as a trusted advisor to drive enterprise AI adoption and technical strategy.

Requirements

• 12+ years in software engineering, with 5+ years leading multi-team engineering organizations delivering enterprise AI solutions.
• Expertise in agentic AI/ML systems, orchestration frameworks (LangChain, Semantic Kernel), and LLMOps/MLOps platforms (MLflow, Kubeflow, Azure ML).
• Strong knowledge of vector databases (Pinecone, Weaviate, Milvus) and retrieval pipelines for LLMs.
• Hands-on experience with Azure, Kubernetes, and event-driven architectures (Kafka/Event Hub).
• Strong proficiency with Python and ML frameworks.
• Advanced degree in Computer Science.

Culture & Benefits

• Solution-oriented culture focusing on measurable business value and continuous improvement.
• Environment that encourages experimentation, innovation, and a growth mindset.
• Collaborative atmosphere with empowerment across engineering, data science, and product functions.
• Focus on professional development and staying current with emerging technologies.