Technical Director AI and Automation

Job Overview

The Technical Director of AI & Automation is responsible for translating enterprise AI and automation strategy into technical architecture and delivery, leading the design and implementation of scalable solutions across the organization. This role demands deep technical expertise in artificial intelligence, machine learning, and intelligent automation platforms, with a strong emphasis on cloud-native (including Microsoft Azure and Amazon Web Services (AWS) soltutions).

The ideal candidate will have hands-on experience with AI/ML model development, deployment pipelines, and MLOps practices, as well as advanced proficiency in automation platforms such as Microsoft Power Automate and Automation Anywhere. This leader will be responsible for driving innovation through scalable and modular AI architectures, ensuring robust integration and practices- with enterprise systems and standards, and fostering a culture of technical excellence in automation, data, and AI/ML engineering.

The Technical Director will work in close partnership with internal IT stakeholders (architecture, applications, infrastructure analytics, IT operations, informatics), business partners (operations, clinical or shared business services), and external partners (vendors, academic or others) to accomplish program goals for AI, Automation, and AI governance. The ideal candidate will possess excellent communication and technical skills, enabling them to effectively engage with stakeholders at all levels and across the enterprise.

A deep understanding of healthcare data and regulatory requirements is essential, as this leader is responsible for ensuring compliance and maintaining the highest standards of data security and privacy. The candidate should have hands-on experience working with classic statistics, classic AI/ML approaches, and generative AI frameworks including their optimization; deploying AI models in production environments; leading development with teams leveraging a range of programming languages (e.g., Python, R, Java), AI tools (e.g., Tensor Flow, PyTorch, scikit-learn) and associated enabling technologies including familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud).

Responsibilities

* AI and Automation Strategy Execution:
Deliver technical execution of the organization's AI and automation strategy, ensuring alignment with overall business goals and objectives as well as judicious capability development.

* AI and Automation Solution Implementation:
Oversee the deployment of AI solutions often working with solution owner(s), including machine learning models, natural language processing including generative AI, and computer vision applications

* AI Performance Monitoring:
Establish and utilize metrics and processes to monitor the performance and impact of AI solutions, directing adjustments as needed to optimize outcomes and minimize organizational risk. Work with operational owners on business case development.

* Innovation:
Stay current with AI, automation, analytics, and data and AI governance advancements and trends, driving continuous improvement and innovation within the organization.

* Collaboration and AI/Automation Value:
Work closely with IT, data science, and business teams to identify promising AI and automation opportunities, integrate AI and automation solutions into existing and redesigned workflows. Monitor solution outcomes to demonstrate solution value.

* Global High Performing Team:
Create a team culture focused on high performance through effective recruitment, coaching and development, team modeling and design, work assignments focused on improving and growing our key talent, and enabling the success and empowerment of the team. Foster a culture in which creativity and innovation thrive; identify changes in the technology stack or processes that will motivate innovative problem-solvers. Ability to lead a global, technical staff of internal resources and strategic partners.

Previous experience working closely with external vendors to internalize capabilities and build competency of internal staff in data technologies

Required Qualifications

* Bachelor of Science IT, Computer Science, Data Science, Biostatistics Healthcare, Business or related field OR an equivalent combination of experience, education and/or training.

* 8 years related IT experience and a strong understanding of data science, data integration technologies and their applications

* 5 years experience managing enterprise software development teams

* 5 years leadership including direct mentoring and managing of others, including managing leaders of others

* Knowledge of clinical data integration including RESTful and SOAP oriented web service development, ETL technology (SSIS, Data Stage, Informatica, etc.), interface protocol models (HL7, X12), EDI standards, ESB (Mule Soft) knowledge.

* Experience with database management, data warehousing, SQL, master data management, and data modeling including healthcare common data models.

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