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About This Role
### Redefine the future of customer experiences. One conversation at a time.
At Nextiva, we’re reimagining how businesses connect, bringing together customer experience and team collaboration on a single, conversation centric platform. Powered by AI, driven by human innovation.
Our culture is forward thinking, customer obsessed and built on the belief that meaningful connections drive better business outcomes. Whether it’s through our signature Amazing Service®, the technology we create, or the experiences we cultivate, connection is at the core of who we are.
If you’re ready to collaborate with incredible people, make an impact, and help businesses everywhere deliver truly amazing experiences, this is where you belong.
Location: This is an onsite role based at Nextiva’s Scottsdale headquarters (9451 E. Via de Ventura, Scottsdale, AZ 85256\). Working together onsite strengthens how we operate, enabling faster decisions, clearer communication, and stronger execution, so you can make a greater impact and move work forward with speed and clarity.
In\-Office Expectation: This role is expected to work onsite five days per week, supporting a highly collaborative, in\-person team environment.
About Nextiva
Nextiva is an AI\-first company delivering one connected experience from first click to daily use. We serve over 100,000 businesses, and the brand is how most of them meet us. We recently launched a full rebrand — new identity, new visual system, new voice — and we're still in the early stages of rolling it out across every surface and channel.
We're building a marketing team that works differently. AI isn't an experiment for us. It's the default.
About the Role
You'll run day\-to\-day creative production for Nextiva's marketing department — and fundamentally change how it gets done.
This is a hands\-on leadership role. You execute on landing pages, campaign assets, ad creative, video, and brand storytelling — working within the creative direction set by the Creative Director and CMO. But the real job is applying your taste, creativity, and judgment to AI so that the output exceeds what either could produce alone. AI on its own produces average work. You make it exceptional — and in doing so, you automate the mundane creative tasks that used to require headcount, so we can scale campaigns and marketing efforts without growing the team.
Your work starts in AI. Ideas get explored in Claude or Cursor before they ever touch a design application. You use Cursor or Claude to build landing pages, prototype workflows, and ship creative prototypes in code.
You'll manage a small team of designers and videographers, mentor them on AI\-native workflows, and keep the Creative Director and CMO aligned on progress, priorities, and output quality.
We're looking for someone whose taste and creative instincts are what make AI work above average — someone who can take direction, bring real creative thinking to AI\-driven workflows, elevate the output, and keep the team moving every day.
What You'll Do
- Design and produce high\-quality creative across marketing. Execute on landing pages, campaign creative, digital ads, email, video, and brand moments. Stay close to the work. Concept it, review it, and push it until it meets the bar..
- Build AI\-first creative workflows. Redesign how creative gets produced — from ideation through final delivery. Use AI for concepting, copywriting, and creative exploration. Use AI to build and ship pages, assets, and tools. Automate the repetitive production work — ad variations, asset resizing, template\-based builds — so the team spends its time on creative decisions, not mechanical ones.
- Manage and develop the creative team. Run the team day\-to\-day with a strong player\-coach approach. Manage and assign work, unblock people, and keep projects on track. Onboard the team to AI\-native tools and processes. Set the expectation that AI\-generated work is the starting point, not the finish line and show them what it looks like to refine it to a high standard.
- Define what great AI\-assisted creative looks like. Document workflows, prompts, and patterns that produce consistently strong results. Share them across the team and the broader marketing org. Raise the bar for everyone, not just your direct reports.
- Steward and expand the brand. We've recently launched a new brand identity. You'll be responsible for maintaining it, enforcing consistency as it rolls out across more surfaces, and expanding the system with considered, tasteful additions as needs arise. New templates, new asset types, new channels — all should feel like they belong to the same brand.
- Connect creative output to business results. Partner with growth, demand gen, and product marketing to ensure creative work drives awareness, engagement, and pipeline. Use performance data to refine direction. Balance speed and experimentation with intentional quality.
- Scale creative output without scaling the team. Create repeatable, AI\-driven processes for producing brand\-consistent creative at volume. The goal is to multiply what a small team can deliver — more campaigns, more channels, more variations — without adding headcount. Define review standards, asset templates, and production workflows that make this possible.
What You Need
- Proven creative leadership in a marketing, brand, or agency environment — you've led teams and stayed hands\-on in the work
- Strong design taste and visual judgment — you know what great looks like and you push until you get there
- Fluency in Cursor and Claude as primary creative tools — you use them daily to build, not just brainstorm
- Experience producing marketing creative: landing pages, digital ads, campaign assets, brand design, video
- A portfolio of functioning projects you've built with AI tools — not static mockups or visual comps. We want to see working landing pages, live tools, shipped creative, or interactive prototypes. Show us what you've made that actually runs.
- Comfort working in code — you don't need to be an engineer, but you can build and ship a working page in Cursor without one
- A builder mindset — you improve systems and processes, not just individual deliverables
- Clear communication and the ability to take creative direction from senior leadership and translate it into team execution
- Comfort moving fast, iterating in the open, and treating feedback as fuel
Nice to Have
- Experience working within an established brand system — maintaining consistency, extending it thoughtfully, and knowing when to push boundaries vs. hold the line
- Familiarity with design systems, tokens, or component libraries
- Background in B2B SaaS, tech, or high\-growth environments
- Experience evaluating and adopting new creative technology for a team
- Interest in motion design, video production, or interactive storytelling
Why This Role
Most companies are still debating whether to use AI in creative. You'll be building the playbook. You'll have direct access to senior leadership, a clear mandate to rethink how things are done, and a team ready to move. The work you produce will be visible — every landing page, every campaign, every brand moment.
This is a role for someone who wants to define what AI\-native creative looks like at a company that's already committed to it.
Nextiva DNA (Core Competencies)
Nextiva’s most successful team members share common traits and behaviors:
- Drives Results: Action\-oriented problem solvers who quickly bring clarity and simplicity to ambiguity, challenge the status quo, and lead meaningful change; celebrating wins to fuel momentum. They act swiftly and pragmatically, learning and improving as they go.
- Critical Thinker: Data\-driven, forward\-thinking individuals who identify key drivers, anticipate risks, and deliver clear recommendations. They confidently leverage AI and automation to reduce friction, improve decision\-making, and focus on higher\-value work.
- Right Attitude: Collaborative, competitive, and resilient team players who jump in to solve tough problems, learn from setbacks, and foster a culture of service, respect, and care for customers and teammates.
#### Total Rewards
Our Total Rewards offerings are designed to allow Nexties to take care of themselves and their families so they can be their best, in and out of the office.
Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses.
- Health: Multiple health plan options to suit your needs, including medical, dental, vision, and telemedicine coverage
- Insurance: Life, disability, and supplemental indemnity plans
- + ️ Work\-Life Balance: Flexible Time Off for salaried employees, PTO for hourly employees, Paid Sick Time, Paid Parental Bonding Leave, and holiday pay
- Financial Security: 401(k) with company match, Health Savings Accounts with company contributions, Dependent Care FSA
- Wellness: Employee Assistance Program (EAP) and comprehensive wellness initiatives
- Growth: Access to ongoing learning and development opportunities and career advancement
At Nextiva, we're committed to supporting our employees' health, well\-being, and professional growth. Join us and build a rewarding career!
Nextiva is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Nextiva participates in the E\-Verify Program where and as required by law. .
\#LI\-MP1 \#LI\-Onsite
Founded in 2008, Nextiva has grown into a global leader trusted by over 100,000 businesses and 1M\+ users worldwide. Headquartered in Scottsdale, Arizona, and with teams across the globe, we're the future of customer experience and team collaboration through our AI\-powered, conversation\-centric platform.
Want to see what life at Nextiva is all about?
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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Nextiva, 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Nextiva AI Hiring
Nextiva has 3 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Based in Scottsdale, AZ, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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