Director of Engineering Job at Evergreen, Atlanta, GA

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  • Evergreen
  • Atlanta, GA

Job Description

As Associate Director of Engineering, you will lead the design, and engineering of enterprise-grade agentic AI solutions and frameworks for Evergreen.AI. This role requires a proven leader who can scale engineering teams, define technical strategy, and ensure operational excellence for production systems-not just PoCs and pilots. You will leverage your experience in technical architecture, global delivery leadership, and AI enablement to build secure, resilient, and compliant solutions for Fortune 1000 clients.

Key Responsibilities:

  • Engineering Leadership: Build and lead high-performing engineering teams across regions; establish career frameworks, mentorship programs, and succession planning.
  • Platform & Framework Ownership: Define Evergreen.AI’s agentic AI architecture, including multi-agent orchestration, LLM knowledge management, and enterprise integration patterns.
  • Delivery Excellence: Drive production readiness-runbooks, observability, SLAs, and resiliency patterns for multi-region deployments.
  • Technical Strategy: Partner with Product and Architecture to align roadmaps with business outcomes; evaluate emerging technologies for scalability and compliance.
  • Operational Governance: Implement secure SDLC, CI/CD, LLMOps/MLOps, and DevSecOps practices; ensure adherence to SOC 2, ISO 27001, HIPAA, and GDPR standards.
  • Client Engagement: Support executive briefings, architecture reviews, and technical pre-sales; act as a trusted advisor for enterprise AI adoption.
  • Innovation & Enablement: Champion responsible AI principles; contribute to reusable accelerators, reference architectures, and delivery templates.

Qualifications:

  • 12+ years in software engineering, with 5+ years leading multi-team engineering organizations delivering enterprise-grade AI solutions.
  • Proven experience in technical architecture and global delivery leadership for Fortune 1000 clients.
  • Expertise in agentic AI systems, orchestration frameworks (LangChain, Semantic Kernel), and LLMOps/MLOps platforms (MLflow, Kubeflow, Azure ML).
  • Strong knowledge of data and knowledge management for LLMs, including retrieval pipelines and vector databases (Pinecone, Weaviate, Milvus).
  • Hands-on experience with cloud platforms (Azure preferred), container orchestration (Kubernetes), and event-driven architectures (Kafka/Event Hub).
  • Familiarity with observability tools (Prometheus, Grafana, ELK) and resiliency patterns (circuit breakers, chaos engineering).
  • Exceptional leadership, communication, and stakeholder management skills.
  • Advanced degree in Computer Science

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