Enterprise Architect

2 weeks ago


Atlanta, Georgia, United States Intellectt Inc Full time

Role:
Enterprise Architect (AI/ML)

Location
: Atlanta, GA--Onsite

Duration
: Full Time

Key Responsibilities:

  • Define and execute the company's enterprise technology roadmap aligned with business objectives and AI-first strategy.
  • Lead the architecture, design, and implementation of scalable, secure, and cloud-native systems.
  • Drive AI/ML and Generative AI initiatives, leveraging LLMs, OpenAI/GenAI platforms, and emerging technologies to enhance products and operations.
  • Architect and oversee solutions leveraging AWS, Azure, or GCP, ensuring high availability and performance.
  • Establish enterprise architecture standards, governance, and best practices across teams.
  • Collaborate with product, data, and business leadership to define technical strategy and priorities.
  • Guide teams on data platforms, MLOps, AI governance, and model lifecycle management.
  • Ensure security, compliance, and data governance across cloud and AI systems.
  • Evaluate and adopt new tools, frameworks, and platforms to drive innovation and operational efficiency.
  • Mentor and lead architecture, engineering, and data science teams.

Required Skills & Qualifications:

  • 10+ years of progressive experience in software engineering, architecture, and technology leadership.
  • Strong hands-on experience with AI/ML and Generative AI (LLMs, prompt engineering, model deployment).
  • Proven expertise in cloud platforms: AWS, Azure, or GCP.
  • Solid understanding of enterprise, cloud-native, and data-driven architectures.
  • Experience with Python, Java, and modern backend frameworks.
  • Knowledge of data platforms, APIs, microservices, and event-driven systems.
  • Strong understanding of security, scalability, and performance optimization.
  • Proven ability to influence stakeholders and lead cross-functional teams.
  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Preferred Qualifications:

  • Experience with MLOps, CI/CD, DevOps, Docker, and Kubernetes.
  • Exposure to AI governance, responsible AI, and compliance frameworks.
  • Familiarity with big data, analytics, and real-time data processing.
  • TOGAF or similar enterprise architecture certification is a plus.
  • Experience working in startup or large-scale enterprise environments.

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