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About This Role
QUALIFICATIONS
- 3\+ years of experience in a technology management, platform operations, IT leadership, or related role
- Demonstrated people management experience with direct reports; proven ability to coach, develop, and retain talent
- In depth understanding and passion for excellence in the WWT Core Values.
- Strong program management skills with experience driving cross\-functional initiatives from strategy through execution
- Excellent communication and presentation skills — written, verbal, and visual — for both technical and non\-technical audiences including senior executives
- Ability to think creatively and bring innovative ideas to complex, ambiguous problems
- Familiarity with AI platforms and tools (e.g., Microsoft Copilot, Claude, Glean, ChatGPT, Google Gemini, or similar)
- Understanding of data privacy, security, and AI governance principles
- Self\-motivated with the ability to work independently with minimal supervision
- Demonstrated ability to manage multiple priorities in a fast\-paced, evolving environment
- Applicants must be authorized to work in the United States. We are unable to provide sponsorship for this position.
Preferred
- Experience as a program manager for enterprise\-wide adoption, change management, or enablement programs
- Hands\-on experience administering enterprise AI platforms (Copilot, Glean, Claude, or similar)
- Experience building and managing community or champion networks across a large organization
- Experience with adoption analytics, usage reporting, and data\-driven decision making
- Familiarity with AI governance frameworks and responsible AI principles
- Bachelor's degree, preferably in Computer Science, Management Information Systems, Business, or a related field; a combination of education, training, and experience may be considered in lieu of a degree
COMPENSATION \& BENEFITS
Certain states and localities require employers to post a reasonable estimate of the salary range. A reasonable estimate of the current base pay range for this position is $126,800 to $158,500 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that are not included in the base pay.
The well\-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full\-time employees:
- Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
- Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
- Paid Time Off: PTO and Sick Leave (starting at 20 days per year) \& Holidays (10 per year), Parental Leave, Military Leave, Bereavement
- Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program
We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All!
If you have any questions or concerns about this posting, please email taposting@wwt.com.
\#LI\-REMOTE
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Requirements:
WHY WWT?
At World Wide Technology, we work together to make a new world happen. Our important work benefits our clients and partners as much as it does our people and communities across the globe. WWT is dedicated to achieving its mission of creating a profitable growth company that is also a Great Place to Work for All. We achieve this through our world\-class culture, generous benefits and by delivering cutting\-edge technology solutions for our clients.
Founded in 1990, WWT is a global technology solutions provider leading the AI and Digital Revolution. WWT combines the power of strategy, execution and partnership to accelerate digital transformational outcomes for organizations around the globe. Through its Advanced Technology Center, a collaborative ecosystem of the world's most advanced hardware and software solutions, WWT helps clients and partners conceptualize, test and validate innovative technology solutions for the best business outcomes and then deploys them at scale through its global warehousing, distribution and integration capabilities.
With over 12,000 employees across WWT and Softchoice and more than 60 locations around the world, WWT's culture, built on a set of core values and established leadership philosophies, has been recognized 14 years in a row by Fortune and Great Place to Work® for its unique blend of determination, innovation and creating a great place to work for all.
Want to work with highly motivated individuals on high\-performance teams? Join WWT today!
WHAT IS THE IT AI CENTER OF EXCELLENCE AND WHY JOIN?
The IT AI Center of Excellence (AI COE) is a hub for AI strategy, platform management, and enablement — driving the adoption of AI tools and capabilities across WWT. The Workforce AI team sits at the center of this transformation, managing WWT's portfolio of workforce AI platforms and ensuring employees across the company can take full advantage of the latest AI tools embedded in their everyday workflows. This spans platform administration, licensing governance, feature enablement, adoption analytics, and employee training — as well as operating the AI Competency Center (AICC), WWT's organization\-wide program for building AI skills and capabilities across business units.
As the Workforce AI \& AICC Manager, you will lead a team of analysts, shape the strategy for how WWT's employees experience AI in their daily work, and serve as the program manager for the AI Competency Center — a high\-visibility program with executive stakeholders. You will own the roadmap for some of WWT's most widely used AI platforms, influence how AI tools are adopted at scale, and help build a culture of AI fluency across the organization. If you are energized by innovation, leadership, and enterprise\-wide impact, this is the role for you.
WHAT WILL YOU BE DOING?
As the Workforce AI \& AICC Manager, you will lead the team responsible for overseeing WWT's workforce AI platforms and driving the AI Competency Center program. This is a dual\-charter role: you are both a people manager and a program leader. You will guide a team of AI Platform Analysts while also owning the strategy and execution of the AICC program.
*A strong candidate demonstrates the following competencies:*
- Leadership \& Team Development – Builds, coaches, and grows a high\-performing team of analysts; fosters a culture of ownership, curiosity, and continuous improvement
- Strategic Thinking – Connects day\-to\-day platform work to broader organizational AI goals, balances short\-term needs with long\-term platform vision
- Innovation \& Creativity – Brings new ideas to life; identifies opportunities to expand AI adoption in novel and impactful ways
- Executive Communication – Comfortable presenting to senior leaders and executives; synthesizes complex information into clear, actionable narratives
- Program Management – Manages multiple workstreams simultaneously; keeps stakeholders aligned and deliverables on track
- Collaboration – Builds strong relationships across IT, business units, and vendor partners; serves as a trusted advisor and connector
- Data\-Driven Mindset – Uses adoption analytics and usage data to inform decisions, surface insights, and demonstrate platform value
- DOER – Favors action over continued discussion; not afraid to get hands on keyboard to move ideas forward
RESPONSIBILITIES
People Management
- Lead, mentor, and develop a team of AI Platform Analysts supporting WWT's workforce AI platforms
- Set clear goals and expectations; conduct regular 1:1s, performance reviews, and career development conversations
- Foster a high\-performance team culture grounded in ownership, collaboration, and continuous learning
- Coordinate work assignments and balance team capacity across platform support, enablement, and AICC responsibilities
- Identify hiring needs and participate in recruiting efforts as the team grows
Workforce AI Platform Oversight
- Oversee and maintain the operational health, licensing, and configurations of all Workforce AI platforms (Copilot, Claude, Glean, and similar)
- Track and evaluate new features, product updates, and roadmap developments across managed platforms; communicate implications and opportunities to the team and stakeholders
- Perform foundational setup, administrative tasks, and platform configuration as needed
- Coordinate with teams to collect, build, and maintain adoption and usage analytics for all platforms
- Manage vendor relationships and serve as the primary point of escalation for platform issues
- Assess and onboard new AI tools and platforms as the enterprise AI landscape evolves
- Ensure platforms comply with WWT's security, governance, and acceptable use requirements; partner with Legal, Compliance, and Security as needed
- Maintain documentation for platform operations, governance policies, and runbooks
User Enablement \& Training
- Champion best practices for responsible and effective AI use across WWT
- Oversee the design and delivery of training programs, onboarding materials, and self\-service resources for employees using Workforce AI platforms
- Partner with business units to identify use cases, drive meaningful adoption, and share success stories
- Gather and act on user feedback to continuously improve the platform experience
- Create and maintain learning content including guides, videos, FAQs, and skills libraries
AICC Program Management
*In addition to platform oversight, this role leads the AI Competency Center (AICC) — WWT's organization\-wide program for building AI skills and capabilities across business units.*
- Own the strategy, roadmap, and execution of the AICC program from end to end
- Serve as the primary program manager, driving planning, coordination, and communication across all AICC workstreams
- Build and maintain strong relationships with AICC business unit leadership and executive stakeholders; provide regular program updates and strategic recommendations
- Manage and grow the AICC Champions Network — empowering champions to evangelize AI skills and use cases within their respective teams
- Plan, organize, and execute AI innovation events including hackathons, AI showcases, and enablement workshops
- Define and track key AICC program metrics; report on progress, adoption trends, and outcomes to senior leadership
- Ensure the AICC program is aligned to the AI COE's broader mission and WWT's organizational AI strateg
Salary Context
This $126K-$158K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At World Wide Technology, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($142K) sits 15% below the category median. Disclosed range: $126K to $158K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
World Wide Technology AI Hiring
World Wide Technology has 13 open AI roles right now. They're hiring across AI Software Engineer, AI Product Manager, AI/ML Engineer, Data Scientist. Positions span Remote, US, New York, NY, US, Edwardsville, IL, US. Compensation range: $93K - $250K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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