Enterprise AI Lead Architect

CACI International; United States; Hybrid; USD 115,000 - 252,000; Full time

Job summary

AI Engineering Lead role at CACI International seeks a visionary technologist to architect and oversee enterprise AI implementations for DHS OIG. You will guide teams, define architectures, and establish governance for secure, compliant AI across cloud environments.

Leadership in LLMs, generative AI, and production ML operations is essential, with hands‑on guidance across design, development, and deployment of mission‑critical analytics tools.

Qualifications

• Bachelor's degree with 15+ years in AI/ML, software engineering, or related field (or equivalent).
• Proven leadership in architecting enterprise AI/ML solutions and leading cross‑functional teams.
• Deep expertise in LLMs, generative AI, Azure OpenAI, and enterprise AI platforms.

Responsibilities

• Provide technical leadership and architectural direction for all AI capabilities, including OIGChat and enterprise AI platform services across Azure Government and Commercial environments.
• Oversee secure, governed access to Government‑approved AI models (Azure OpenAI, Azure AI Foundry, other providers).
• Lead design, development, and architecture of mission‑specific AI applications for investigative analytics and oversight use cases from concept through production.
• Establish and enforce model governance, cost management, and responsible AI frameworks with monitoring, dashboards, and guardrails.

Skills

Leadership

AI architectures

LLMs / Generative AI

Azure AI services

Python

Education

Bachelor's degree + 15 years experience

Tools

LangChain

Semantic Kernel

TensorFlow

PyTorch

Azure OpenAI

Azure AI Foundry

Job description

AI Engineering Lead role at CACI International seeks a visionary technologist to architect and oversee enterprise AI implementations for DHS OIG. You will guide teams, define architectures, and establish governance for secure, compliant AI across cloud environments.

Leadership in LLMs, generative AI, and production ML operations is essential, with hands‑on guidance across design, development, and deployment of mission‑critical analytics tools.