Sr Dir - AI and Automation

What success looks like in this role:

Team Integration

- Merge two specialized technical teams (30–40 members total) into a unified organization with aligned objectives, streamlined processes, and a collaborative culture. - Facilitate synergy between Generative AI specialists (focused on LLMs, diffusion models, and creative AI applications) and RPA/Automation Engineers (focused on process optimization and bot deployment). - Address potential cultural and technical clashes by establishing common frameworks for project management, communication, and success metrics. - Drive cross-pollination of skills through structured training programs, such as teaching automation engineers about generative AI capabilities for enhancing bot interactions, and exposing AI specialists to process mining techniques for identifying automation opportunities. - Foster a shared vision by creating joint initiatives, like developing AI-powered automation workflows that leverage generative models for dynamic decision-making in real-time processes. - Implement team-building activities and regular syncs to build trust and ensure both teams feel valued in the merged structure, targeting a post-merger retention rate of 95% or higher. Technical Strategy - Design and oversee the development of integrated solutions that combine generative AI with automation, such as AI-driven chatbots for customer service that trigger automated workflows for issue resolution. - Lead the creation of scalable architectures for deploying generative AI models within automated processes, ensuring seamless integration with existing enterprise systems. - Establish governance frameworks for ethical AI use in automation, including bias mitigation in generative outputs and transparency in automated decision-making. Process Optimization - Streamline current development processes to enhance efficiency, agility, and overall speed by implementing modern methodologies like Agile or DevOps tailored to AI and automation projects. - Identify and eliminate bottlenecks in the development lifecycle, reducing time-to-deployment for AI models and automation solutions through automated testing, continuous integration, and iterative feedback loops. - Standardize tools and workflows across teams to minimize context-switching and accelerate delivery timelines while maintaining high-quality outputs. Productivity Accountability - Achieve annual savings targets through AI-enhanced automation initiatives that reduce manual effort and improve operational efficiency. - Develop and track key performance indicators (KPIs) such as time-to-resolution for automated processes, error rates in AI-driven outputs, and full-time equivalent (FTE) reductions. Stakeholder Partnership - Collaborate with senior leadership to define quarterly roadmaps that balance innovation with cost-saving goals. - Present data-driven business cases to operations and finance teams, demonstrating the tangible impact of integrated AI and automation solutions.

You will be successful in this role if you have:

- 10+ years of experience leading technical teams in AI and automation domains. - Demonstrated success in merging cross-functional technical teams with high retention rates (above 50% post-merger). - Hands-on expertise in: - Generative AI: Prompt engineering, and implementing ethical AI practices. - RPA/Automation: Process mining, bot orchestration, and integration with legacy systems using tools like UiPath or Automation Anywhere.

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