About
Ryan Brady, marketing engineer
Fifteen-plus years leading enterprise search and growth programs, with a parallel habit of building the software around those programs that makes them run. Background in intelligence analysis.
Based on Long Island, NY. This site is the personal home for the work — builds, writing, the stack, the career.
The person behind the braid
A career spent at the intersection of search, growth, and software
Ryan is a marketing engineer — a marketer who builds scalable systems. Fifteen-plus years inside enterprise search and growth programs, with a consistent habit of building the software around the work rather than waiting for someone else to do it.
In addition to the Strategy Director role, the work has transformed into building a wide range of internal tools and workflows across the company — de facto PM throughout: owning roadmaps, scoping requirements, doing the builds, shipping the thing. Marketing-engineer instincts paired with the muscle memory of running product end-to-end.
Before enterprise consulting, he co-founded a DTC e-commerce brand and grew it from zero to acquisition through pure organic strategy — millions in revenue and a social following past 10 million.
Earlier in his career, Ryan did intelligence analyst work for the Society of Former Special Agents of the FBI and completed an intelligence-division internship with the Nassau County Police Department — OSINT research, formal intelligence reports, and analytical frameworks for complex investigations. Those pattern-recognition and rigor habits are the same ones that show up later in the technical work.
Ryan studied Intelligence Studies at Mercyhurst University, one of the top intelligence analysis programs in the country.
See a problem, ship a solution.
Have an idea, ship a feature.
Career
Expertise
Capabilities and the kinds of work I've shipped along the way.
Building with AI
AI engineering
Where most of the recent work lives — production AI systems, the tooling around them, and the engineering side of building with LLMs.
Production LLM content systems
Built end-to-end pipelines for content generation — topic discovery, brief creation, drafting, evaluation, and publish-ready output. The shape of the work, not just the model call.
Prompt engineering & context design
Designed prompt structures, context libraries, retrieval flows, and output specifications. Where output quality actually moves — more than model choice.
NLP at scale
Built classification, clustering, summarization, and topic-extraction systems that turned messy text data into the signals product and editorial decisions actually run on.
Embeddings & retrieval
Worked on semantic search, retrieval-augmented generation, and evidence-grounded output that doesn't hallucinate its citations.
Computer vision
Built segmentation, classification, and OCR pipelines — turning 'point a camera at a thing' into structured data. The rare-coin scanner is the working example.
AI agent architecture & operation
Decomposing workflows into what agents actually need: skills, tools, evals, memory, feedback loops. Systems that run on their own and improve without someone kicking them off.
Custom AI tools & automation
Shipped workflow-specific AI tools — order validation, content ops, internal knowledge systems, dashboards. Most of my career has been shaped by builds like these.
Web development & front-end engineering
Shipped marketing sites, internal tools, and AI front-ends in TypeScript / Next.js / React over the years. This site is the working portfolio piece.
Product leadership
Building product
The other lens on the work — when the marketing-engineer hat becomes the product-manager hat. Roadmapping, scoping, prioritizing, and partnering with engineering to ship.
Product roadmapping & ownership
Defining product vision and roadmap for SEO, AI-visibility, and brand-monitoring tooling. Translating customer behavior, technical constraints, and business goals into prioritized product work.
Customer + data → product decisions
Turning user behavior, session data, and search-intent research into product hypotheses and shipped features. The 'what to build next' muscle.
Cross-functional team leadership
Working across engineering, design, analytics, and SEO stakeholders. Translating between disciplines and aligning teams around a shared outcome.
Experimentation & measurement
Running A/B tests, defining success metrics, and using outcomes to validate hypotheses and iterate. Pre-decided KPIs over post-hoc storytelling.
Search, visibility & data
Search & data
The career foundation — enterprise search, AEO/GEO, marketing data infrastructure, and the intelligence-analysis methodology that runs underneath all of it.
AEO, GEO & AI-search visibility
Worked on how brands appear across ChatGPT, Perplexity, Gemini, and Google AI Overviews — measuring citation share, accuracy, sentiment, and source coverage.
Enterprise & technical SEO
Fifteen-plus years inside the technical layer of how big sites work in search — crawlability, indexation, JS rendering, schema, and site architecture at scale.
Marketing data infrastructure
Built dashboards, instrumentation, and attribution layers — the data plumbing that lets a marketing program tell whether what it's doing is actually working.
Brand intelligence & OSINT methodology
Applied intelligence-analyst training to brand and online-presence problems — sourcing, attribution, network analysis, and threat-surface mapping.
Operator & founder
Marketing operator
The other half of marketing engineering — the operator skills that ship growth: DTC founder credential, organic growth, content, lifecycle, and exec-level communication.
0-to-1 founder experience
Co-founded and grew a DTC e-commerce brand from zero to acquisition. Five years running organic growth, content, and lifecycle marketing — the operator side of the work.
Organic growth strategy
Grew a DTC brand from zero to acquisition on pure organic — content, SEO, owned channels, no paid spend. Built the earned-channel playbook that compounded into the exit.
Content strategy & editorial governance
Built editorial frameworks at enterprise content scale — taxonomy, intent design, source-of-truth mapping, brand voice, and the governance layer that keeps a hundred-piece-per-quarter program coherent.
Lifecycle marketing & email
Grew a DTC list to 300,000+ segmented subscribers with full lifecycle automation — welcome flows, abandoned-cart, post-purchase, win-back. The retention-compounding side of growth.
Strategic communication & executive narrative
Translated technical complexity into the strategic narrative that C-suites and boards actually need — briefs, decks, frameworks, and the conversation pattern that makes complex AI work decision-ready.
Recommendations
What colleagues say
Pull-quotes from people I've worked alongside.
“Ryan sees the full system, connects dots others miss, and elevates strategy with a clarity and precision that's rare. He doesn't just solve problems — he reframes them in ways that change the trajectory.
“The AI tools he's built have reshaped how our entire team works. They've saved us hundreds of hours. He builds sophisticated solutions faster than anyone I've seen.
“Ryan identifies inefficiencies nobody else sees and invents smarter systems to fix them. The automation work he's done has allowed our team to focus on higher-value priorities and accelerated our impact dramatically.
“Ryan's presence elevates meetings, deliverables, thinking, and morale. He's the partner everyone wants on their team — steady, strategic, supportive, and deeply committed to shared success.
“Ryan fosters collaboration and creates safe spaces for questions. His mentorship has boosted the confidence and capabilities of everyone on the team. Ryan makes the impossible feel achievable.
“Consistently goes above and beyond — showing up in urgent moments, stepping in when needed, and always delivering exceptional results. Ryan's reliability and responsiveness are unmatched.
Side projects
Things I build for myself
The projects that never had a brief — stuff I made because the problem was mine to solve.