AI Career Path - AI Job Descriptions

In current plans for technology deployment, over two-thirds of all companies looking at Artificial Intelligence (AI) and Machine Learning (ML) as a priority. A limiting factor is finding individuals with the skills and experience to meet those goals. Universities, over time, have provided graduates that meet the needs of businesses to meet their technological needs resources currently are not geared toward providing their graduates with the tools they need to be viable candidates for these positions.

The challenge faced by CIOs and recruiters is to define who should be on the AI ML team. Adding to the complexity of the problem, the requisitions and job descriptions that are being used are insufficient and inaccurate.

The first step is to have a job description which defines the education, training, and experience required.

Salaries for Artificial Intelligence and Machine Learning IT Pros

We have defined eleven (11) specific sets of responsibilities that need to be addressed at the AI process is implemented in an enterprise'.

Chief Artificial Intelligence Officer - a C-suite executive overseeing a company’s overall strategy, acquisition, implementation, and monitoring of AI and Machine Learning (ML) technology. This role requires a deep understanding of the business, technical expertise, and regulatory awareness. The CAIO must be capable of communicating AI-related information effectively across the organization. However, the role is not solely technical; it demands diverse skills, including AI ethics, understanding, and implementation awareness.
Data Scientist - advocate, evangelize, and build data-fueled products that help enterprise customers improve outcomes. The Data Scientist is detail-oriented and is an expert on the data sets utilized by the enterprise. The Data Scientist provides insight into leading analytic practices, designs and leads iterative learning and development cycles, and ultimately produces new and creative analytic solutions that will become part of the enterprise’s core deliverables.
Manager Artificial Intelligence - provides the strategic direction on compliance for the design, development, and implementation of AI models into operational workflows, including helping draft and review the procedures that support a compliance system. Additional responsibilities may include guiding AI teams with project planning, system architecture, risk management, verification & validation, and continuous monitoring.
Manager Database - provides the strategic direction on compliance for the design, development, and implementation of AI models into operational workflows, including helping draft and review the procedures that support a compliance system. Additional responsibilities may include guiding AI teams with project planning, system architecture, risk management, verification & validation, and continuous monitoring.
Manager Information Architecture - faces the challenge of translating short and long-range strategic plans for Information architecture into the design and implementation of current and future applications.
Project Manager Artificial Intelligence - responsible for overseeing the Artificial Intelligence/Machine Learning (AI/ML) project team. This group is responsible for the enterprise’s AI/ML applications, cyber currency controls, and AI/ML processing systems that form the basis of this initiative. This responsibility includes processing security, cyber currency management systems, resource monitoring and reporting, and development of specialized programs. The Project Manager Artificial Intelligence coordinates AI/ML processing software issues with other IT organizations including applications and operations.
Artificial Intelligence Architect - is responsible for the overall management and direction of all technical services functions associated with Artificial Intelligence (AI) and Machine Learning (ML) applications. The manager works within the Information Technology arena.

The Manager AI helps implement infrastructure that advances the digital strategy for AI and Software across the enterprise. The Manager AI is a thought leader in the application of AI in the enterprise’s industry, with an initial focus on guiding engineering processes for the safe, effective, and ethical implementation of AI and ML.
Artificial Intelligence Developer - deals with algorithms and codes that can train a machine to behave like a human. One of their primary responsibilities is to be well-versed in applied math, probability, statistics, and similar topics so they can successfully and efficiently program machines. They are skilled in aspects of computer and web-based programming, user experience (UX) design, project management, and client communication.

The Artificial Intelligence Developer’s focus is on both the front and back ends of Artificial Intelligence / Machine Learning (AI/ML) applications. This includes underlying database work, user-facing construction, and client-focused communication aimed at the planning and maintenance of projects.
Large Language Model Engineer - deals with algorithms and codes that can train a machine to behave like a human. One of their primary responsibilities is to be well-versed in applied math, probability, statistics, and similar topics so they can successfully and efficiently program machines. They are skilled in aspects of computer and web-based programming, user experience (UX) design, project management, and client communication.

The Large Language Model Engineer’s focus is on both the front and back ends of LLM applications. This includes underlying database work, user-facing construction, and client-focused communication aimed at the planning and maintenance of projects.
Large Language Model Developer - esponsible for developing innovative solutions to challenging problems, including command and control and high-integrity solutions. Perform complex analysis, design, development, testing, and debugging of computer software for distinct product hardware or technical service lines of businesses. Perform LLM design, operating architecture integration, and computer system selection. Operate on multiple systems and apply knowledge of one or more platforms and programming languages.
Robotics Technician - implements robotics utilizing rapidly changing robotics technologies. At the same time conforming with the associated technology standards and meets the enterprise’s operational needs

The Individual should be aware of robotics best practices and lead the company to implement them where possible.