Interested in this AI/ML Engineer role at Fastly?
Apply Now →About This Role
Fastly helps people stay better connected with the things they love. Fastly’s edge cloud platform enables customers to create great digital experiences quickly, securely, and reliably by processing, serving, and securing our customers’ applications as close to their end\-users as possible — at the edge of the Internet. The platform is designed to take advantage of the modern internet, to be programmable, and to support agile software development. Fastly’s customers include many of the world’s most prominent companies, including GitHub, Yelp, Paramount, and JetBlue.
We're building a more trustworthy Internet. Come join us.
Posting Open Date: 08/11/2026
Anticipated Posting Close Date\*: 09/11/2026
- *Job posting may close early due to the volume of applicants.*
Director, Product Marketing – Security, AI and Emerging Technology
This Director leads the product marketing function across two of Fastly's dynamic and fastest evolving product areas: Security and AI. While these domains serve different buyer personas and address different use cases on the surface, they share a critical strategic thread. Both represent Fastly's highest growth opportunity to expand beyond its CDN foundation, and both operate in markets where the competitive landscape is shifting rapidly.
This is a highly externally facing, narrative driven role. This leader will work to establish Fastly as a credible, trusted player in markets where buyers have no shortage of alternatives.
Reporting to the VP of Product Marketing, you will lead and manage a team of product marketers covering security and AI/emerging technology, guide go\-to\-market strategy and execution, partner closely with Analyst Relations, and act as a cross\-functional evangelist for these categories, serving as a key voice in the market.
What You'll Do:
- Team Leadership: Lead and manage a team of product marketers spanning Security and AI \& Emerging Technology.
- GTM Strategy \& Execution: Guide the strategic creation and execution of go\-to\-market plans for security and AI/emerging technology product launches.
- Narrative \& Messaging: Develop Fastly's overarching security story and AI/emerging technology narrative, and validate that both resonate with target buyers around the problems that we solve with our solutions.
- Analyst Relations: Partner with the Head of Analyst Relations to support the AR program for security and AI, ensuring the analyst community understands Fastly's narrative and value propositions in both categories.
- Executive \& Company Visibility: Represent the security and AI/emerging technology product lines in company QBRs.
- Partner \& Channel GTM: Collaborate with Partner Marketing and Channel Sales teams to prioritize and support partner GTM efforts.
- Sales Enablement: Partner with the enablement team to create sales trainings and other assets used in sales cycles.
- Market Positioning: Partner with Portfolio Intelligence to apply competitive intelligence and technical differentiation insights to effectively position Fastly's security and AI products and features.
- Customer \& Buyer Insights: Ensure proof points, value delivery, and customer insights cultivated by the Advocacy team and other parts of the org are accurately represented and activated across Product Marketing assets and deliverables.
- Customer Advocacy Support: Partner with the Advocacy team on the creation and review of customer proof materials (case studies, testimonials, references) to ensure they reflect accurately, on narrative security and AI positioning.
- Cross\-Functional Alignment: Collaborate cross\-functionally with Product Management, Sales, and Marketing to ensure product strategy, messaging, and packaging are aligned and effective.
- Content \& Campaign Input: Provide input on and create unique assets with Growth Marketing and Campaigns for use across the buyer journey including within select verticals.
- Category Evangelism: Partner with Portfolio Intelligence to find a differentiated angle in a crowded competitive field for security and AI, shape how that angle is told, and deliver that message to the market in public presentations.
What We're Looking For:
- 12\+ years of relevant product marketing experience in security, AI/ML, or related infrastructure categories, including 5 years leading product marketing teams.
- Technical understanding of modern approaches to cloud and application security; familiarity with AI/ML infrastructure and governance concepts.
- Strong analytical abilities, with experience sizing and prioritizing market opportunities.
- Excellent copywriting, editing, and communication skills.
- Highly competent and confident presenter and trainer, comfortable with frequent interaction with customers, prospects, and industry analysts.
- Track record of success leading product marketing teams and delivering on sales enablement commitments while driving alignment with cross\-functional stakeholders.
- Ability to juggle multiple projects in a dynamic, high pressure environment.
- Attention to detail and discipline to not only follow but also establish policies and processes that guide the full product marketing team.
We’ll be super impressed if you have experience in any of these:
- Experience building category narratives in markets where the vendor is an upstart.
- Familiarity with Gartner, Forrester, or IDC evaluation processes for security and/or AI categories.
- Passion for driving positive business outcomes with a deep understanding of customer business needs and key market trends.
Work Hours: This position will require you to be available during core business hours.
Work Location(s) \& Travel Requirements:
The preferred locations for this position are:
- San Francisco, CA
- New York, NY
- Denver, CO
Fastly currently embraces a largely hybrid model for most roles which allows employees flexibility to split their time between the office and home.
There is a strong preference for Hybrid near a local office. However, we may be willing to consider remote candidates within the US.
This position may require travel as required by your role or requested by your manager.
SF / LA Fair Chance Ordinance Statement
Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Salary:
The estimated salary range for this position is $194,040 to $273,936\.
Starting salary may vary based on permissible, non\-discriminatory factors such as experience, skills, qualifications, and location.
This role may be eligible to participate in Fastly’s equity and discretionary bonus programs.
Benefits:
We care about you. Fastly works hard to create a positive environment for our employees, and we think your life outside of work is important too. We support our teams with great benefits that start on the first day of your employment with Fastly. Curious about our offerings?
We offer a comprehensive benefits package including medical, dental, and vision insurance. Family planning, mental health support along with Employee Assistance Program, Insurance (Life, Disability, and Accident), a Flexible Vacation policy and up to 18 days of accrued paid sick leave are there to help support our employees. We also offer 401(k) (including company match) and an Employee Stock Purchase Program. For 2026, we offer 12 paid local holidays, 12 paid company wellness days.
Why Fastly?
- We have a huge impact. Fastly is a small company with a big reach. Not only do our customers have a tremendous user base, but we also support a growing number of open source projects and initiatives. Outside of code, employees are encouraged to share causes close to their heart with others so we can help lend a supportive hand.
- We value diversity. Growing and maintaining our inclusive and diverse team matters to us. We are committed to being a company where our employees feel comfortable bringing their authentic selves to work and have the ability to be successful \- every day.
- We are passionate. Fastly is chock full of passionate people and we’re not ‘one size fits all’. Fastly employs authors, pilots, skiers, parents (of humans and animals), makeup geeks, coffee connoisseurs, and more. We love employees for who they are and what they are passionate about.
We’re always looking for humble, sharp, and creative folks to join the Fastly team. If you think you might be a fit please apply! A fully completed application and resume or CV are required when applying.
*All job applications must be submitted through our official careers site at* *www.fastly.com/about/careers. We will never request sensitive information, such as your Social Security number, bank account or credit card information during the application process. All official communication will come from an @fastly.com* *or @**recruiting.fastly.com* *email address.*
*Fastly is committed to ensuring equal employment opportunity and to providing employees with a safe and welcoming work environment free of discrimination and harassment. Our employment decisions are based on business needs, job requirements and individual qualifications.* *All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, family or parental status, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.*
*Consistent with the Americans with Disabilities Act (ADA) and federal or state disability laws, Fastly will provide reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact your Recruiter, or the Fastly Employee Relations team at* *[email protected]* *or 501\-287\-4901\.*
*Fastly collects and processes personal data submitted by job applicants in accordance with our* *Privacy Policy. Please see our* *privacy notice for job applicants.*
Salary Context
This $194K-$273K 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 Fastly, 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 in Demand for This Role
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 ($233K) sits 9% above the category median. Disclosed range: $194K to $273K.
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.
Fastly AI Hiring
Fastly has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $273K - $273K.
Location Context
AI roles in Denver pay a median of $199,950 across 66 tracked positions. That's 7% 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 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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