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About This Role
Education Qualifications
- Bachelor's degree in information technology or related field preferred.
- A combination of education, training and experience may be considered in lieu of a degree.
Work Experience
- 5\+ years of progressive experience in a related field is required.
- 2\+ years direct work experience in the Project Engineering capacity
- 3\+ years hands on experience configuring and troubleshooting issues on a Cisco network.
- CCNA or CCNP strongly preferred.
- Experience at working both independently and in a team\-oriented, collaborative environment is essential with the ability to elicit cooperation from a wide variety of sources, including upper management, clients, and other departments.
Knowledge, Skills, and Abilities
- Resolves issues by diagnosing problems, determining possible resolutions and implementing effective solutions.
- Demonstrates the discipline of planning, organizing and managing resources and activities to achieve specified outcomes within a clearly defined timeframe and standards.
- Identifies documentation needs and develops technical reference documentation in accordance with standards and styles.
- Communicates with clarity and precision, presenting complex information in a concise format that is audience appropriate.
- Serves in a “player coach” role by managing, reviewing and conducting the day\-to\-day work in a specific technical domain area; applies domain knowledge to develop solutions to problems.
- Leverages technical knowledge of products to meet customer needs and understands market segments as well as market data trends.
- Leverages technical knowledge of products to meet customer needs and understands market segments as well as market data trends.
- Ability to design engineering drawings such as rack elevations and cable run list schematics, detailing all in\-rack connections (Example: power, data networking and storage)
- Knowledge of industry standards and best practices for structured cabling systems using various cable types (cat 5e, cat 6, multi\-mode and single\-mode fiber, etc.)
- Knowledge of data center electrical requirements and conversions (i.e. Kilowatts, Amps, phases, UPS, etc.)
- Familiarity with Cisco Unified Communication Manager \- configuration, installation and troubleshooting (CUCM, CTS Manager, Interoperability, MCU, Device registrations, SIP and H.323\).
- Familiarity with design fundamentals, and initial setup and configuration tasks associated with the build\-out of VMware vSphere solutions.
- Understanding of server platforms, including Windows Server, ESXi, Redhat, LINUX and UNIX operating systems.
- Proficient understanding of hardware platforms, such as HP Blade chassis, and HP standalone servers, Cisco UCS B and C series, Cisco WAVE and WAS.
- Familiarity with Local and Wide Area Networks and Data Communications including the internet, DHCP, and DNS.
- Solid understanding of current data center and network technologies that are commonly running as part of the IT infrastructure for Fortune 500 companies.
- Can conform to shifting priorities, demands and timelines through analytical and problem\-solving capabilities and the ability to prioritize in a high\-pressure environment
- Other skills include process management, decision making, managing vision and purpose and learning on the fly
- This role includes assignment of work for specific WWT customers. Some customers have specific on\-boarding requirements, including background check and drug testing requirements that go beyond WWT's requirements. Ability to meet these requirements may be necessary for continued employment, depending on needs of the department.
Essential Physical Demands
- Sitting: Frequently
- Standing: Constantly
- Walking: Frequently
- Stooping, kneeling, crouching: Frequently
- Reaching 30” to 72”: Constantly
- Eye/hand coordination: Constantly
- Lifting (up to 50lbs): Frequently
- Lifting Overhead: Occasionally
- Carrying: Frequently
- Twisting/Turning: Frequently
- Fine Motor Coordination (keying, labeling): Occasionally
- Fine Motor Coordination (pinch, tool use, stripping wire): Frequently
- Fine Motor Coordination (pick \& place small parts): Constantly
- Gripping/Grasping: Frequently
- Climb (more than 2 steps): Occasionally
Working Environment
- Work near moving machinery: Constant
- Fumes or airborne particles: Frequent
- Toxic or caustic chemicals: Frequent
- Risk of electrical shock: Frequent
- Extremes: heat (non\-weather): Occasional
- Non\-climate controlled environment : Constant
Is this role an individual contributor or does it have direct reports?
Individual Contributor
Level of Autonomy
Work is accomplished without considerable direction. Exercises judgment in selecting methods, techniques, and evaluation criteria in obtaining results. Exerts significant latitude in determining objectives of assignment. Takes calculated risks with consultation from the expert
Compensation/ Benefits
Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base salary range for this position is $74,400\-$93,000 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 salary.
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 \& Holidays, Parental Leave, Sick Leave, Military Leave, Bereavement
- Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program
World Wide Technology is an Equal Opportunity Employer. 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\-KH1
\#LI\-hybrid
Requirements:
Solutions Engineer \- NAIC2
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!
A Brief Overview
Perform intake, solution validation and forecast evaluation for engineering and other technical activities relating to the project. This person will have direct contact with customers and vendors. The engineer will assist with pre\-sales on\-board, quote validation, and deliver solutions before transitioning to execution operations.
Job Responsibilities
- Interface with Customers, PMs, and CSEs to identify and provide inputs and technical guidance to ensure design optimization
- Engage with pre\-sales teams to provide technical guidance on lab capabilities to ensure more accurate project intake and gauge of technical level of effort
- Develop and communicate technical project design to project engineer to ensure successful execution of technical solutions per specifications and/or configuration instructions utilizing both industry and WWT best practices.
- Drive global collaboration and program standardization.
- Work closely with project teams during the execution of ETOs (Engineer to Order), providing SME\-level expertise.
- Drive the project's progress, from kick\-off to final approval.
- Provide consulting and support for the configuration of multiple vendor networking, wireless, and collaboration devices.
- Communicate project status to both internal and external stakeholders on a continuous basis.
- Serve as an escalation point for complex troubleshooting of defective devices, logical issues, or systematic errors on a wide range of technologies.
- Provide technical guidance, knowledge transfers, and mentorship to peers.
- Review and provide SME\-level expertise throughout customer ETOs.
Salary Context
This $74K-$93K range is below 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 ($83K) sits 50% below the category median. Disclosed range: $74K to $93K.
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.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
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.
Frequently Asked Questions
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