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About This Role
Customer Success VP / Head of Search & AI Visibility
Full Time VP / Head of Search & AI Visibility About Milestone
Milestone Inc. is a leading Digital Experience Software and Services company dedicated to providing comprehensive solutions across all touch points that enhance customer engagement and drive business growth. Milestone mission is to pioneer the distribution and visibility of content with an innovative platform that drives discovery, personalized experiences, and conversions powered by data and AI. We pride ourselves on our collaborative culture and commitment to excellence in everything we do and are certified Great Place to Work.
About Role
Milestone is seeking a highly respected search practitioner, commercial leader, and innovation-driven strategist to lead our Search & AI Visibility practice.
This is a senior leadership role at the intersection of product, customer success, sales, and market leadership. You will shape how Milestone evolves its search-related products and solutions across technical SEO, CMS, local search, schema, entity optimization, GEO, and AI visibility. You will also serve as a trusted advisor to customers, partners, and the industry.
The ideal candidate brings deep technical SEO expertise, experience across both agency and in-house environments, a strong point of view on the future of search, and a proven ability to influence revenue growth through search-led innovation.
You will Lead
- Search strategy and innovation.
- Product influence and roadmap contribution.
- Customer advisory and executive consulting.
- Commercial support for strategic opportunities.
- Industry thought leadership and advocacy.
- Internal enablement across sales, product, marketing, and customer success.
Key Responsibilities
Lead Milestone's Omnichannel Solution offerings including but not limited to technical SEO, content, paid, digital experience, local etc.
Product Strategy & Innovation
- Partner with Product and Engineering teams to shape Milestone's Search, GEO, Schema, Entity, Local, and AI Visibility platforms
- Translate market needs, customer insights, and industry shifts into product opportunities.
- Evaluate and test emerging technologies in search, AI visibility, GEO, schema, entity optimization, knowledge graphs, and agentic discovery.
- Lead or support proof-of-concepts and validation programs that inform solution development.
Customer Advisory & Solution Leadership
- Advise enterprise customers on search strategy, visibility, and AI readiness.
- Lead workshops, executive briefings, and strategic discovery sessions.
- Help customers improve discoverability, structured visibility, and measurable search performance.
- Translate complex technical concepts into business outcomes that matter to senior stakeholders.
Revenue Growth & Commercial Leadership
- Partner with Sales to support enterprise opportunities, renewals, and expansion.
- Contribute to pipeline creation and strategic deal acceleration.
- Help define solution narratives and value propositions that improve win rates.
- Support customer retention and adoption through solution-led engagement.
Industry Advocacy & Thought Leadership
- Represent Milestone at industry events, webinars, podcasts, and conferences.
- Publish thought leadership, frameworks, and insights on the future of search and AI visibility.
- Build enablement materials, playbooks, and training for internal teams.
- Strengthen Milestone's credibility with customers, partners, and the broader search community.
- Build strategic relationships with Google, Microsoft, OpenAI, Anthropic, Industry influencers and Search communities
Enablement & Scale
- Create repeatable frameworks, playbooks, and methodologies
- Enable Sales, Customer Success, Product and Marketing Teams
- Build training programs around Technical SEO, GEO, AI Visibility, Schema, Entity Optimization and Agentic Web Readiness
- Develop customer-facing collateral, presentations, and solution guides
hat success looks like
In the first 12 to 18 months, success in this role will look like:
- Milestone is recognized as a category leader in AI Visibility, GEO, and Agentic Search
- Increased adoption of Search and AI Visibility solutions
- Strong internal enablement and repeatable playbooks.
- Measurable contribution to pipeline, expansion, and strategic revenue.
- Recognized external thought leadership and market credibility.
- Strong partnerships established across the search and AI ecosystem
- Customers view Milestone as a trusted advisor for the future of Search, AI Discovery, and Agentic Commerce
Ideal Candidate Profile
Someone very similar to a modern search leader who combines practitioner depth, product thinking, commercial acumen, and industry influence - equally comfortable auditing JavaScript rendering issues, advising a Fortune 500 CMO, influencing a product roadmap, speaking on stage at SMX, and helping close a seven-figure enterprise opportunity.
Required Experience & Qualifications
- 15+ years of experience in Technical SEO, enterprise search, search strategy, digital experience, or search product leadership.
- Experience in both agency-side and in-house enterprise environments.
- Deep expertise in technical SEO, enterprise SEO, local search, schema, structured data, entity optimization, AI search, and GEO.
- Proven experience working with Product, Engineering, Sales, and Customer Success teams.
- Strong executive presence, communication skills, and presentation ability.
- Demonstrated ability to connect technical strategy to commercial impact.
Preferred Experience
- Leadership experience in search or SEO organizations.
- SaaS or digital experience platform background.
- Experience with multi-location, hospitality, retail, financial services, or other complex enterprise environments.
- Public thought leadership through speaking, publishing, or community involvement.
What We Offer
- Competitive salary and performance-based incentives.
- Comprehensive benefits package.
- Opportunity to work in a collaborative and innovative environment.
- Career growth and professional development opportunities.
- A chance to be part of a global team that makes a significant impact in the industry.
How to Apply
Interested candidates are invited to submit their resume and a cover letter outlining their qualifications and vision for the role plus previous experience align with key attributes, responsibilities, clear wins or learnings.
Why Milestone
Founder Led, Award Winning Platform, Great Place to Work, Engaging Culture.
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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At Milestone Inc., 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 $212,000 based on 11,866 positions with disclosed compensation.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Milestone Inc. AI Hiring
Milestone Inc. has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in US.
Location Context
AI roles in Austin pay a median of $207,800 across 271 tracked positions. That's 3% below the national 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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