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About This Role
Key Responsibilities:
Maximize Account Engagement
- Engage as a trusted C\-suite advisor to shape and advance Microsoft Cloud and AI transformation opportunities in partnership with WWT account and services sales teams, with an emphasis on Pharma, Utilities, Financial Services or Insurance
- Proactively identify and qualify high\-impact transformation opportunities that align with customers' Cloud and AI strategies
- Collaborate across WWT solution areas to craft integrated, outcome\-driven strategies that position WWT as the Microsoft partner of choice
- Lead cross\-functional teams to architect scalable, secure, and high\-performing Microsoft Cloud and AI solutions — with an emphasis on data platform and agentic AI architectures — that support enterprise transformation goals
Solutions Leadership
- Work with WWT account teams to educate on Microsoft Cloud and AI capabilities and drive business development and sales
- Work with Sales engineers/Cloud consultants to review and validate understanding of customer requirements and translate initial scope into actionable items
- Build relationships across the organization to scope and deliver cross\-functional and cross\-domain solutions such as Digital, Security, AI, Analytics, Automation, and Enterprise Architecture
- Spearhead the strategic design of innovative solutions by leveraging deep knowledge of the evolving technology landscape and maximizing internal WWT capabilities
- Actively pursue business opportunities at large, complex customers; work with clients and internal WWT Teams to develop and negotiate statements of work, including project scope, deliverables, timelines, and costs.
- Partner with delivery and sales leadership to ensure solutions seamlessly transition from proposal to execution, enabling rapid value realization and measurable business outcomes
- Develop a trusted partner relationship with Microsoft technical sales leaders, expanding opportunities across accounts and regions
Market and Thought Leadership
- Represent WWT as an industry thought leader in executive client forums, industry events, and strategic roundtables, particularly within the Microsoft Cloud Data and AI ecosystem
- Provide competitive and market intelligence to shape WWT's strategic positioning and future solution development
- Drive increased client engagement and pipeline growth by serving as a visible industry leader who influences strategic buying decisions
Technical Leadership
- Serves as a trusted advisor to clients, adeptly understanding their unique needs and crafting tailored recommendations that drive value and foster long\-term partnerships
- Deliver with strong analytical, quantitative, and conceptual thinking skills and effective interpersonal and communication skills to ensure successful client projects \& team performance
- Represent WWT's technical expertise to team members and customers through an in\-depth knowledge of Microsoft Cloud and AI technologies, including Microsoft Fabric, Azure AI Foundry, Agent 365, OneLake, and the Microsoft IQ intelligence layer
- Maintain expert level knowledge on WWT solution offerings and industry cloud technologies including the completion of assigned courses and relevant certification exams when applicable.
- Stay current with emerging technologies and advancements within existing technologies
Qualifications:
- A minimum of 15 years progressive experience in a related field required
- A minimum of 10 years of experience selling, scoping, designing, deploying, and/or implementing Microsoft Cloud and AI technologies aligned to industry best practices
- Bachelor's Degree in a related field (i.e. Computer Science, Information Systems, or Engineering)
- Deep expertise consulting on large scale transformation with enterprise customers, with experience in one or more of the following: Pharma, Utilities, or Healthcare
- Deep specialized expertise in Microsoft Cloud and AI ecosystem products and solutions, including Microsoft Fabric, Azure AI Foundry, Agent 365, OneLake, Microsoft IQ, and Azure OpenAI Service
- Experience with complex commercial models including strategy\-led consulting, implementation and managed services, and transformation programs
- Proven ability to shape and close large strategic advisory engagements that lead to downstream implementation services
- Proven ability to act as a thought leader in executive client settings, industry forums, and strategic briefings
- Proven ability to provide market intelligence and competitive insights to inform customer strategy and internal GTM initiatives
- High proficiency at collaborating, managing conflicting interests, and dealing with ambiguity
- Strong leadership qualities: capable of engaging effectively with senior executive stakeholders and earning their technical trust; able to inspire and align the WWT team around a shared technical vision
- Intellectually curious: the desire to understand constantly evolving technology solutions and how they connect to business and IT outcomes
- Assertive, collaborative, self\-starter with emotional intelligence as well as the capacity to learn and synthesize new information to provide customers and the WWT account team with useful insights
- Flexible with proven ability to conform to shifting priorities, demands and timelines through analytical and problem\-solving capabilities
- Self\-directed, with the ability to adapt to change and competing demands
Strongly Desired Skills:
- Expert\-level industry certifications related to Azure Cloud Platform (i.e. Azure Solutions Architect Expert, Azure DevOps Engineer Expert, Microsoft Fabric Analytics Engineer)
- Familiarity with one or more of the following:
+ Cloud container management and Kubernetes platforms (i.e. AKS)
+ Cloud strategy and adoption patterns
+ Cloud modernization and migration
+ Application architecture and development in the cloud (i.e. .NET Core, Java, etc. in Azure Functions, App Services or containers)\\
+ Core Cloud infrastructure – Networking (i.e. ExpressRoute, vWAN), Security (i.e. Azure Firewall, 3rd party ISVs), Compute, and Storage
+ CI/CD pipeline development for automated cloud infrastructure using Infrastructure as Code (i.e. ARM/Bicep, Terraform, Ansible), application code deployments (i.e. GitOps) and associated agile tools (i.e. Azure DevOps, JIRA, etc.)
- Experience working with and integrating other vendors such as Snowflake, Databricks, VMware, Palo Alto, NetApp, Red Hat and other cloud technologies and ISVs
- Experience and working knowledge of infrastructure concepts and technologies such as Virtualization, Networking, Data Center, and Security
Want to learn more about Consulting Services? Check us out on our platform: https://www.wwt.com/consulting\-services
Travel: 20%
Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base pay range for this position is $225,000 \- $235,000 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 is not included in the base pay.
The well\-being of WWT employees is essential. 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 (Medical \& Prescription), Dental, and Vision Care, Onsite Health Centers (MO \& IL), Employee Assistance Program, Wellness program
- Financial Benefits: Competitive Pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Flexible Spending Accounts, Tuition Reimbursement
- Paid Time Off: PTO \& Holidays, Parental Leave, Medical Leave, Military Leave, Bereavement, Day of Caring
- Additional Perks: Family Planning Benefits, Nursing Mothers Benefits, Voluntary Legal, Voluntary Supplemental Accident/Illness/Hospital, Voluntary ID Theft, Pet Insurance, Employee Discount Program
Note: This is not an all\-encompassing list and should not be used as a complete description of the plan's benefits. For more information, see our US benefits website at wwt.com/us\-benefits.
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 require accessibility accommodation(s) or adjustment during any stage of the hiring process, please let your WWT Recruiter know. The recruiter will work with you to understand your needs and help ensure an accessible experience throughout the interview process.
World Wide Technology is an Equal Opportunity Employer.
If you have any questions or concerns about this posting, please email [email protected].
Requirements:
*\*This position will require someone who is located in the northeastern region of the United States (NY/NJ)\**
Why WWT
World Wide Technology (WWT) strives to make a new world happen. WWT's work benefits clients and partners as much as it does its people and community across the globe.
Founded in 1990, WWT brings together strategy, deep technical expertise and world\-class partnerships to help public and private sector organizations design, build and scale intelligent AI, digital, cybersecurity, cloud and infrastructure solutions. Through its Advanced Technology Center (ATC)—a collaborative ecosystem featuring state\-of\-the\-art hardware and software—WWT enables clients and partners to conceptualize, test and validate innovative technology and then deploy solutions at scale using its global integration and distributions capabilities.
With more than 14,000 team members and over 60 locations globally, WWT's culture—grounded in core values and leadership philosophies—has been recognized by Fortune® and Great Place to Work for its commitment to innovation, trust and creating a great place to work for all. WWT provides products and services to large enterprise, global service provider and public sector clients in up to 130 countries across six continents. Softchoice, a World Wide Technology company, supports commercial and SMB markets in the U.S. and Canada.
Want to work with highly motivated individuals on high\-performance teams? Join WWT today!
What is the Solutions Consulting \& Engineering Team and why join?
Solutions Consulting \& Engineering is an organization that is customer\-focused and solutions\-led. We deliver end\-to\-end and emerging solutions to drive customer satisfaction and increase profitability and growth. Our world\-class management consulting, delivery excellence, and engineering brilliance enable our success. We embody the OneWWT mindset by bringing the right talent at the right time from anywhere within WWT to solve our customer's problems. Our goal is to bring together business acumen with full\-stack technical know\-how to develop innovative solutions for our clients' most complex challenges.
Position Overview:
As a Director – Microsoft Cloud and AI Solution Architect, you function as both a consultant and technical leader. As a consultant, you will meet with the business and IT leaders of our clients, understand their ambitions, and pain points, and develop a vision of how to best solve their problems. As a technical leader, you will actualize the vision by solutioning complex engagements involving WWT's service offerings and technical teams — bringing the credibility to engage executive stakeholders and the depth to lead the architecture.
You will partner with WWT account teams, executive sponsors, services sales, and C\-suite stakeholders to shape and close Microsoft Cloud and AI engagements that transform their technology landscape and provide meaningful business value while driving adoption of Microsoft solutions.
This role requires deep subject\-matter expertise in Microsoft Cloud and AI technologies — with a strong foundation in core platforms including Microsoft Fabric, Azure AI Foundry, and Agent 365 — as well as the ability to stay ahead of rapidly emerging solutions such as Microsoft IQ (Fabric IQ, Foundry IQ, and Work IQ) and the broader agentic AI ecosystem. Candidates must demonstrate a strong understanding of industry trends and competitive landscapes, and the ability to articulate strategic value in executive boardroom settings. You will help shape the customer vision, influence large transformation opportunities around data platform modernization, agentic AI at enterprise scale, and governed multi\-agent architectures, and position WWT as a trusted strategic partner driving measurable business impact. In this role, you will also serve as an industry thought leader, bringing forward cross\-industry perspectives and innovation insights to shape client strategy.
Salary Context
This $225K-$235K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% 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 $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($230K) sits 7% above the category median. Disclosed range: $225K to $235K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
World Wide Technology AI Hiring
World Wide Technology has 11 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Remote, US, San Francisco, CA, US, New York, NY, US. Compensation range: $80K - $235K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. 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: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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.
Frequently Asked Questions
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