411 Locals is looking for a Director of Applied AI and Automation to oversee the comprehensive delivery of practical, production-ready AI and automation solutions throughout the organization. This role focuses on transforming business challenges into operational systems rather than engaging in research or experimental projects. The successful candidate will integrate IT Development, Business Analysis, and Development QA into a cohesive delivery framework, ensuring that AI and automation initiatives are effectively implemented, scalable, and reliable, thereby transforming IT from a cost center into a significant operational and revenue driver.

Requirements

• 8–12+ years of experience in software engineering, automation, and/or applied AI roles
• 5+ years of experience leading cross-functional delivery teams (Development, Business Analysis, and QA)
• Proven track record of delivering production AI or automation systems
• Strong understanding of system architecture, APIs, integrations, automation frameworks, and applied AI/ML implementation
• Ability to translate business needs into functional systems and drive delivery under real operational constraints
• Experience in supporting digital marketing, sales, or call-center ecosystems is a strong plus

Nice to Have

• Experience with ITIL-aligned operational practices (practical, not theoretical)
• Strong financial and ROI mindset
• Familiarity with cloud platforms and scalable automation
• Comfort working in high-growth, fast-changing environments

Key Responsibilities

1. Own Applied AI & Automation Delivery (End-to-End)

   • Lead the design, build, deployment, and maintenance of AI-driven and automation systems in production.
   • Ensure each initiative has a clear business owner, measurable KPIs, and defined success and failure criteria, eliminating “proof-of-concept purgatory.”

2. Unified Ownership of IT Development, Business Analysis & QA

   • Merge Development, Business Analysis, and QA into a single execution pipeline.
   • Ensure business requirements are accurately translated into technical specifications and that QA is integrated early in the process.
   • Enforce disciplined SDLC practices with speed and accountability.

3. Business-Driven Automation Strategy

   • Collaborate with business leaders to identify manual workflows, bottlenecks, and high-error, high-cost processes.
   • Prioritize automation initiatives based on ROI, risk reduction, and revenue enablement.

4. Operational Excellence & Reliability

   • Implement standards for system reliability, monitoring, incident response, and regression testing for AI-driven systems.
   • Take ownership of post-deployment accountability.

5. AI That Delivers Value (Not Hype)

   • Apply AI where it significantly improves outcomes, including workflow automation and decision support.
   • Evaluate AI tools pragmatically: build when necessary, buy when quicker, and discontinue when ineffective.

6. Governance, Metrics & Accountability

   • Establish clear governance for AI usage, automation logic, data quality, and change management.
   • Define and track KPIs related to delivery speed, automation coverage, error reduction, cost savings, and revenue enablement.

7. Team Leadership & Capability Building

   • Lead and develop teams of Developers, Business Analysts, and QA Engineers.
   • Foster a culture of ownership, clarity, and execution within the teams.

Key Performance Indicators (KPIs)

• Automation Impact: Reduction in manual effort, errors, and cycle time
• Delivery Velocity: Time from requirement to production
• System Reliability: Uptime, incident frequency, regression rates
• Business Value: Cost savings and revenue enablement from AI/automation
• Team Effectiveness: Retention, skill growth, delivery consistency.

If you are a builder-leader who thrives in a fast-paced environment and is ready to make a significant impact, we encourage you to apply.