Director, AI Engineering
New
P
Precisely US JobsData Integrity
100% remote anywhere in the USFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 10+ years in software engineering; 2+ years leading or mentoring engineering teams
- Required Skills
- Software ArchitecturePrompt Engineering
Requirements
- 10+ years in software engineering with current, deep technical fluency and active production coding.
- 2+ years leading or mentoring engineering teams (formal management or tech-lead experience).
- Daily use of AI-assisted developer tools (GitHub Copilot, Claude Code, Cursor, or equivalent).
- Strong architecture skills in cloud-native AI on Microsoft Azure (Azure AI Services, Azure OpenAI, Entra ID, Microsoft Graph).
- Demonstrated ability to co-architect across platform, data, and enterprise application teams.
- Track record of translating ambiguous business problems into shipped AI solutions.
- Experience establishing AI governance, evaluation, and quality frameworks.
- Ability to communicate complex technical concepts to executive and non-technical audiences.
Responsibilities
- Design and operationalize agentic AI systems with multi-step workflows, orchestration frameworks, and human-in-the-loop patterns.
- Architect and build AI systems including agentic workflows, RAG pipelines, evaluation harnesses, orchestration layers, and prompt engineering.
- Prototype new AI patterns and capabilities to stay ahead of the rapidly evolving landscape.
- Set technical standards through code reviews, design documentation, and reference implementations.
- Hire, mentor, and develop an agile team of AI engineers.
- Represent AI engineering in executive discussions, vendor partnerships (Microsoft, Anthropic), and cross-functional planning.
- Define data requirements for AI models and validate pipeline quality, governance, and freshness.
- Coordinate with Enterprise Applications to integrate AI capabilities into existing business systems (Salesforce, NetSuite, Workato).
- Prioritize AI use cases that enhance enterprise workflows through intelligent automation, predictive insights, and embedded copilot experiences.
- Align on shared data models, integration patterns, and change management processes.
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