Passcreator
Head of AI Enterprise Architecture
Passcreator, Bloomfield, Connecticut, us, 06002
This is a senior contributor role within the Enterprise Architecture organization to lead enterprise efforts from EA’s perspective to transform our business using AI and to significantly improve productivity and efficacy by making right-sized decisions that meet the needs of multiple stakeholders across the organization. The role will work in partnership with the AI Center of Enablement, Senior Technology and Business Executives to guide the strategy of AI solutions and implementations.Responsibilities:
Play a pivotal role in defining the AI architecture vision and selecting appropriate technologies.Research and bring forth recommendations to improve design and technology efficiencies based on business strategy and long-term vision and goals set for the organization.Identify and influence business, technology, AI and digital teams to augment transformation efforts by identifying and piloting use cases. Discuss the feasibility of use cases along with architectural design with business and technology teams to translate the vision of business leaders into realistic technical implementation.Maintain industry and regulatory knowledge and map them to best practices in EA and AI design or recommendations.Partner and support the AI Center of Enablement and senior technology leaders to drive adoption of AI.Requirements & Qualifications:
A highly motivated, collaborative individual with Enterprise Architecture experience in the Artificial Intelligence space, exceptional communication skills and proven experience working with diverse teams of Business and Technical leaders. Qualifications include:Technical Skills:
Leadership experience in building and implementing AI model-driven, enterprise-level business solutions.AI architecture and pipeline planning - Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must.Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow) and ML techniques (such as random forest and neural networks).Advanced knowledge of the modular and open architecture and implementation features.Having automated processes that integrate with web sites, desktop applications, mainframe emulators, ERP software, CRM software.Expertise in a variety of technologies including, but not limited to, WebSphere or Weblogic, J2EE (JSP, Servlets, EJB, XML, Java), .Net, Oracle, DB2, and MS/SQL, Python, NLP, AI/ML algorithms.Experience in working with Cloud and hybrid workloads.Expertise in all phases of software development including design, configuration, testing, debugging, implementation, and support of large-scale, business centric and process based applications.Non-Technical Skills:
Thought leadership – be a change agent to help the organization adopt an AI-driven mindset. Take a pragmatic approach to the limitations and risks of AI, and project a realistic picture in front of IT executives who provide overall digital thought leadership.Collaborative & Advisor mindset – ensure that AI platforms deliver both business and technical requirements, seek to collaborate effectively with data scientists, data engineers, data analysts, ML engineers, other architects, business unit leaders and CxOs (technical and nontechnical personnel), and harmonize the relationships among them.Interpersonal & Organizational Savvy – must be able to influence and develop relationships at all levels of the organization, and be able to navigate in a highly matrixed organization.Cultivates Innovation – Creating new and better ways for the organization to be successful.Strategic Mindset – Seeing ahead to future possibilities and translating them into breakthrough strategies.Instills Trust – Quickly gains confidence and trust of others through honesty, integrity, and authenticity.Attitude – has an attitude or persona of “let’s find a way to do it” attitude – no task is too big or too small.Drives Results – Pushes team and cross functional partners to deliver needed results in tough circumstances and expedited timelines.Manages Complexity – Makes sense of complex and sometimes contradictory information to effectively solve problems.Manages Ambiguity – Operates effectively and drives work forward even when things are not certain or there is no clear way forward.Qualifications:
Bachelor’s degree in Software Engineering, Computer Science, Engineering or related field, advanced degree a plus.10+ years of experience in a software engineering or architecture environment with a specialization in Artificial Intelligence.Excellent knowledge of IT strategic planning and capability development with experience implementing technology strategy and roadmaps; operates with an enterprise mindset.Comfortable with ambiguity and willing to take principled bets; able to “think big” and challenge conventional wisdom regarding technology refresh and hype.Strong leadership, collaboration, and negotiation skills with technical and non-technical groups with a demonstrated ability to lead through influence and build consensus.Execution focused with a “get things done” attitude.Able to process high volumes of complex information, synthesize key themes, and recommend paths forward.Ability to communicate complex technical concepts to senior executives and customers.Ability to build, maintain, and grow high-performing architecture teams.Deep practitioner of Agile and Lean Start-Up methodologies.Demonstrated continuous improvement and continuous learning mindset.Ability to cultivate a culture of openness, transparency, and inclusion.
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Play a pivotal role in defining the AI architecture vision and selecting appropriate technologies.Research and bring forth recommendations to improve design and technology efficiencies based on business strategy and long-term vision and goals set for the organization.Identify and influence business, technology, AI and digital teams to augment transformation efforts by identifying and piloting use cases. Discuss the feasibility of use cases along with architectural design with business and technology teams to translate the vision of business leaders into realistic technical implementation.Maintain industry and regulatory knowledge and map them to best practices in EA and AI design or recommendations.Partner and support the AI Center of Enablement and senior technology leaders to drive adoption of AI.Requirements & Qualifications:
A highly motivated, collaborative individual with Enterprise Architecture experience in the Artificial Intelligence space, exceptional communication skills and proven experience working with diverse teams of Business and Technical leaders. Qualifications include:Technical Skills:
Leadership experience in building and implementing AI model-driven, enterprise-level business solutions.AI architecture and pipeline planning - Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must.Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow) and ML techniques (such as random forest and neural networks).Advanced knowledge of the modular and open architecture and implementation features.Having automated processes that integrate with web sites, desktop applications, mainframe emulators, ERP software, CRM software.Expertise in a variety of technologies including, but not limited to, WebSphere or Weblogic, J2EE (JSP, Servlets, EJB, XML, Java), .Net, Oracle, DB2, and MS/SQL, Python, NLP, AI/ML algorithms.Experience in working with Cloud and hybrid workloads.Expertise in all phases of software development including design, configuration, testing, debugging, implementation, and support of large-scale, business centric and process based applications.Non-Technical Skills:
Thought leadership – be a change agent to help the organization adopt an AI-driven mindset. Take a pragmatic approach to the limitations and risks of AI, and project a realistic picture in front of IT executives who provide overall digital thought leadership.Collaborative & Advisor mindset – ensure that AI platforms deliver both business and technical requirements, seek to collaborate effectively with data scientists, data engineers, data analysts, ML engineers, other architects, business unit leaders and CxOs (technical and nontechnical personnel), and harmonize the relationships among them.Interpersonal & Organizational Savvy – must be able to influence and develop relationships at all levels of the organization, and be able to navigate in a highly matrixed organization.Cultivates Innovation – Creating new and better ways for the organization to be successful.Strategic Mindset – Seeing ahead to future possibilities and translating them into breakthrough strategies.Instills Trust – Quickly gains confidence and trust of others through honesty, integrity, and authenticity.Attitude – has an attitude or persona of “let’s find a way to do it” attitude – no task is too big or too small.Drives Results – Pushes team and cross functional partners to deliver needed results in tough circumstances and expedited timelines.Manages Complexity – Makes sense of complex and sometimes contradictory information to effectively solve problems.Manages Ambiguity – Operates effectively and drives work forward even when things are not certain or there is no clear way forward.Qualifications:
Bachelor’s degree in Software Engineering, Computer Science, Engineering or related field, advanced degree a plus.10+ years of experience in a software engineering or architecture environment with a specialization in Artificial Intelligence.Excellent knowledge of IT strategic planning and capability development with experience implementing technology strategy and roadmaps; operates with an enterprise mindset.Comfortable with ambiguity and willing to take principled bets; able to “think big” and challenge conventional wisdom regarding technology refresh and hype.Strong leadership, collaboration, and negotiation skills with technical and non-technical groups with a demonstrated ability to lead through influence and build consensus.Execution focused with a “get things done” attitude.Able to process high volumes of complex information, synthesize key themes, and recommend paths forward.Ability to communicate complex technical concepts to senior executives and customers.Ability to build, maintain, and grow high-performing architecture teams.Deep practitioner of Agile and Lean Start-Up methodologies.Demonstrated continuous improvement and continuous learning mindset.Ability to cultivate a culture of openness, transparency, and inclusion.
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