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About This Role
We are looking for a Senior Manager, Organic Growth \& AI Search to join Stream on our mission of elevating the quality of apps for billions of users globally.
This is a full\-time role based in our Boulder, Colorado office (hybrid \- 3 days/week in the office expected).
What will you work on
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As Senior Manager, Organic Growth \& AI Search, you’ll own Stream’s organic growth engine across search engines, AI assistants, and our website. You’ll set the strategy for SEO, AI search (AEO), conversion (CRO),and the marketing data infrastructure used to measure them. This is a hands\-on, individual\-contributor role that both sets organic growth strategy and executes it directly, working closely with the marketing, frontend, content, and Developer Relations (DevRel) teams.
Search Engine Optimization (SEO)
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- Own technical SEO for our marketing website and developer docs \- site architecture, crawlability, indexation, schema, structured data, page performance, and resolving technical issues as they surface.
- Run on\-page optimization across the marketing site and docs: content structure, metadata, internal linking, and keyword targeting.
- Build and execute an off\-page and authority program \- link acquisition, digital PR, and partnerships \- to strengthen domain authority.
- Conduct keyword, competitor, and opportunity research to find and prioritize the highest\-value organic plays.
- Partner with content and DevRel to turn editorial and technical content into rankings and qualified organic traffic.
- Monitor organic performance in Google Search Console, Semrush, and analytics tools, and report on qualified traffic, rankings, and signups.
AI Search / Answer Engine Optimization (AEO)
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- Build and maintain tracking for how and where Stream shows up across AI assistants and AI\-search surfaces \- ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.
- Define the methodology and metrics for measuring AI\-search visibility, citation, and recommendation.
- Optimize content and site structure to make Stream more likely to be cited and recommended by LLMs and AI\-search products.
- Evaluate, select, and implement LLM\-visibility tooling \- and build custom tracking where off\-the\-shelf tools fall short.
- Watch emerging AI\-search behavior and adjust strategy as the discovery landscape shifts.
- Partner with DevRel and content to make sure Stream is covered across the prompts that matter.
Conversion \& Web Experience (CRO)
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- Design, run, and analyze A/B and multivariate experiments on live traffic to improve conversion.
- Find and fix friction in conversion funnels, including signup and SDK\-install flows.
- Partner with frontend and content on website and dashboard UX/UI and copy.
- Increase the rate at which organic visitors become signups and active users.
Measurement, Strategy \& Collaboration
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- Help maintain Google Tag Manager (GTM) and GA4, configure event tracking and attribution, and keep marketing measurement accurate and trustworthy.
- Make sure changes across SEO, AEO, and CRO are instrumented cleanly, and troubleshoot tracking and attribution issues independently.
- Set the organic growth roadmap and priorities — you decide what matters, without waiting for a predefined backlog.
- Develop long\-term organic growth strategy and set standards and best practices adopted across the marketing function.
- Specify changes clearly for engineering and content partners, and brief writers on what content needs to hit for SEO and AEO.
- Use AI tools actively day to day to improve your output, speed, and effectiveness.
About You
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You’re a hands\-on operator who sets strategy and then ships it. You move quickly from plan to implementation, instrument your own measurement rather than relying on third parties, and you’re energized by owning an entire growth surface end to end.
You have
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- A demonstrated SEO track record with measurable outcomes across technical, on\-page, and off\-page work \- tied to real traffic and revenue, not just audits and recommendations.
- Experience tracking and optimizing brand visibility inside LLMs and AI Overviews (AEO / AI search), with documented changes and results.
- Hands\-on conversion and experimentation experience \- A/B tests run on live traffic that produced measurable improvements.
- Hands\-on proficiency with marketing data infrastructure, including GTM and GA4 setup, attribution configuration, and independent data analysis.
- The ability to collaborate directly with engineers and content teams \- specifying changes, reading code, and implementing changes yourself.
- Active, applied use of AI tools in your daily work.
Bonus points
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- Experience marketing to developers or technical buyers (API\-first, developer\-tools, or infrastructure companies).
- The ability to implement your own changes (HTML / CSS / JS, templating, basic frontend).
- SQL proficiency and the ability to analyze your own data.
- Strong editorial judgment for content that earns links and citations.
- Experience building LLM\-visibility tracking from scratch.
- Open\-source, community, or developer\-marketing growth experience.
- Agency experience (big plus).
What makes this role exciting?
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- You’ll own Stream’s entire organic growth engine \- SEO, AI search, and conversion \- end to end, setting the strategy and shipping it yourself.
- AI search is being defined right now. You’ll figure out how a developer\-tools company gets cited and recommended by LLMs, often building the tracking from scratch.
- It’s a builder’s role: read code, run experiments, instrument your own measurement \- no waiting on vendors or a backlog.
- You’ll work across marketing, frontend, content, and DevRel, with the autonomy to set standards the whole function adopts.
How is success measured in this role?
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- Growth in qualified organic traffic and signups.
- Measurable improvement in website conversion rates driven by experimentation.
- Increased visibility, citation, and recommendation of Stream across AI\-search surfaces.
- Accurate, reliable marketing measurement and attribution the whole marketing team can trust.
Why join Stream?
====================
- History of success. From Amsterdam to Boulder and Techstars in\-between, Stream has raised over $58\.25M to build the best Chat Messaging \& Activity Feed infrastructure available, with best\-in\-class support.
- Freedom and endless growth opportunities. As a rapidly growing startup (since 2020 we have gone from 30 to 150 employees), Stream gives you unique personal and professional growth opportunities. The opportunity of true ownership and accountability has a massive impact on your career — things you can rarely experience in huge corporations.
- Be on the front line of progress and innovation. While working with cutting\-edge technology, we are passionate about tackling difficult tech problems at scale and creating reusable components for them, empowering engineering teams to ship apps faster, more securely, and with a better user experience.
- They believe in us. Stream is backed by leading VC firms (Felicis Ventures, GGV Capital, 01\.Advisors, Techstars, Arthur Ventures), including backers like Dick Costolo (01 Advisors, ex\-CEO of Twitter), Olivier Pomel (CEO of Datadog), Tom Preston\-Werner (Co\-Founder of GitHub), Nicolas Dessaigne (Co\-Founder of Algolia), and Johnny Boufarhat (Founder and CEO of Hopin).
What we have to offer you
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Stream employees enjoy some of the best job benefits in the industry:
- 19\+ days of paid time off plus 10 paid holidays
- Hybrid work flexibility (3 days a week from the office)
- Free health insurance for the employee and partial coverage for dependents (80% contribution for health, 100% for dental and vision)
- 401k contribution plan with 4% match
- Fitness stipend
- Company equity
- Dog\-friendly office!
- A MacBook Pro provided
- A Learning and Development budget
- Team lunches and plenty of snacks
- RTD pass \+ free parking pass on Pearl Street
- Bi\-weekly office massages
- An office on Pearl Street in downtown Boulder
- 12 weeks paid parental leave for primary parents
- The opportunity to attend or present at global conferences and meetups
- The possibility to visit our office in Amsterdam
*Note:* *this list of benefits applies to Colorado\-based employees and is adjusted per your location of residence.*
Salary (for Colorado only)
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Our salary ranges are based on national averages. We keep wide ranges so we can be flexible and determine compensation based on a number of factors, including the candidate’s skills, level of experience, and location. For Colorado\-based candidates, the salary range for this position is $125k–$135k. Compensation at all other locations will be based on the factors stated above.
Our culture
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Stream has a casual, social culture, and our team is diverse \- we all come from different backgrounds. Today, Stream is a team of over 140 peers from more than 35 countries across the globe.
We value transparency, aim for excellence, and support each other on our way to new victories. Our team consists of some of the strongest talent in the world, which makes Stream a great place to learn and improve your skills.
If you’re interested in becoming a part of what we do, apply for this vacancy now!
*Hybrid office policy:* *applicants based (or relocating to) one of our office locations are expected to work according to the applicable local office attendance policy.*
*Equal opportunity employer statement:* *Stream provides equal employment opportunities to all employees and applicants for employment and prohibits 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.*
*This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.*
*Note for external recruiters:* *We currently have this role covered and do not accept unsolicited agency resumes. We are not responsible for any fees related to unsolicited resumes.*
Salary Context
This $125K-$135K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Stream, 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. This role's midpoint ($130K) sits 28% below the category median. Disclosed range: $125K to $135K.
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.
Stream AI Hiring
Stream has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Boulder, CO, US. Compensation range: $135K - $135K.
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.
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