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About This Role
What You Bring
Required
- 8\+ years in software or platform engineering with 3\+ years managing developers or leading delivery teams
- Demonstrated success managing strong personalities and high\-performing senior ICs — you can point to specific situations where you turned friction into productivity
- Proven ability to deliver under aggressive, changing requirements and deadlines — comfortable renegotiating scope in real time and being the calm center when priorities shift mid\-sprint
- Hands\-on AI development experience — you have personally built with AI coding tools (Claude Code, Copilot, Cursor, or equivalent), you're comfortable leading a team that vibe\-codes, and you can articulate concretely where that approach shines and where it fails (quality drift, security blind spots, unreviewable sprawl) and how you mitigate it
- Experience governing a low\-code / iPaaS platform at scale — intake, build standards, credential/connector governance, and the path from quick automation to a supportable production asset. This can come from Boomi, Retool, Power Automate, Power Platform, Workato, MuleSoft, or a comparable stack; ramping up on our specific tools (Boomi, Retool, Power Automate) is expected on the job, not assumed on day one
- Hands\-on credibility in a modern web stack — you can review a React/TypeScript or Python/FastAPI PR and give substantive feedback
- Experience with cloud\-native deployment on Azure (Container Apps, AKS, or equivalent), CI/CD (GitHub Actions or similar), and secrets/identity patterns
- Track record of shipping and operating production software — including on\-call, incident response, and post\-incident improvement
Preferred
- Experience in a managed services, MSP, or IT operations delivery context
- Direct hands\-on experience with Boomi, Retool, or Power Automate specifically
- Experience coordinating distributed teams across US and India time zones
Nice to Have
- Built or governed reusable AI agent tooling: skills, MCP integrations, multi\-agent workflows, or internal prompt/spec libraries
- Background in Okta/SAML or MSAL/OBO authentication patterns
- Prior success standing up engineering standards in a fast\-growing or newly formed team
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 $150,000\.00 to $170,000\.00 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].
\#LI\-AF1
\#LI\-Remote
Requirements:
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.
About the Role
WWT's Managed Services practice builds and runs an internal application portfolio that powers real customer delivery — from nightly cutover orchestration platforms to pricing and P\&L tooling — alongside a low\-code and automation ecosystem built on Boomi, Retool, and Power Automate. You will lead the development function across both tracks: a pro\-code team building AI\-first on our modern Azure stack, and the low\-code/integration builders automating workflows across the business. This role is as much about people as platforms: you'll manage a range of strong personalities, absorb aggressive and shifting requirements from executive stakeholders, and keep the team shipping through it. We work AI\-native — most code here is written with AI assistance — and we need a leader who has lived that, understands where it accelerates and where it bites, and can build the guardrails to get the best of both.
What You'll Do
- Lead and grow a team of Execution Engineers, Execution Architects, and low\-code builders delivering internal platforms and customer\-facing operational tooling
- Manage a variety of personalities — including strong, opinionated senior technologists — building trust, resolving friction directly, and channeling that energy into output rather than conflict
- Operate under aggressive, frequently changing requirements and deadlines: re\-scope on the fly, communicate trade\-offs to leadership clearly, and protect the team from whiplash without hiding behind process
- Own delivery across a portfolio of production applications built on React/TypeScript, FastAPI/PostgreSQL, and Azure Container Apps — roadmap sequencing, release quality, and incident accountability
- Drive AI\-assisted and "vibe coding" development practices (Claude Code, agentic workflows, spec\-driven builds) as the default way the team works — with a clear\-eyed view of the pros and cons, and standards for review, testing, and guardrails where the risks live
- Own the low\-code and integration portfolio on Boomi, Retool, and Power Automate: intake, prioritization, build standards, connector/credential governance, and the path from quick automation to supportable production asset
- Enforce engineering standards — code quality gates, version pinning, TDD, conventional commits, security patterns (managed identity, Key Vault, HttpOnly JWT/SSO) — without slowing the team down
- Run the operational side of development: sprint cadence, capacity planning across US and India contributors, hiring, and performance management
- Represent the development function in executive reviews — status, risk, and roadmap — with crisp, decision\-ready communication
Salary Context
This $150K-$170K range is in the lower quartile for AI Product Manager roles in our dataset (median: $185K across 167 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At World Wide Technology, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($160K) sits 26% below the category median. Disclosed range: $150K to $170K.
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.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
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).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
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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