Frontend Engineer at Shaped (W22)
$100K - $180K
The real-time retrieval engine for search, feeds, and agents.
New York, NY, US
Full-time
US citizen/visa only
1+ years
About Shaped

Shaped is the fastest path to relevant recommendation and search systems. We help companies turn their behavioral data into truly relevant product and website experiences.

We're a Series A company based in Brooklyn, New York and backed by top investors from Madrona, Y-Combinator, and executives from Meta, Google, Amazon and Uber!

About the role
Skills: JavaScript, React, TypeScript

About Shaped

Shaped is the real-time retrieval engine for search, feeds and agents. We are on a mission to power every product and content experience with world-class search and recommendations. 

Shaped is backed by top-tier investors like Y Combinator and Madrona; with executives from Meta, Google, Amazon and Uber. We’re building an elite team to define the future of how users discover what matters most.

We're excited to work with you. Come build the future of AI with us!

About the role

We’re looking for out founding Frontend Engineer who thrives at the intersection of engineering and product thinking. You’ll own features end-to-end—design, build, launch, and iterate—while obsessing over the customer experience and measurable outcomes. Your work will directly shape how thousands of customers interact with our AI-powered customer service platform.

What you will do

  • Own feature development: from backend services to AI-powered user experiences.
  • Turn customer feedback into product improvements through rapid iteration and experimentation.
  • Collaborate closely with Product, Customer Success, and GTM teams to align engineering decisions with business outcomes.
  • Hold a high bar for code quality: testing, monitoring, and reliability are second nature.
  • Prioritize ruthlessly and navigate changing requirements with autonomy.

Who you are

  • 4-6 years of full-stack/frontend engineering experience - expertise in React, Next.js, and TypeScript
  • Sharp eye for UX
  • Strong familiarity with AI, LLMs, or AI-assisted systems—or a willingness to learn fast
  • Outcome-driven mindset: you measure success in impact, not just shipped features
  • Comfortable collaborating across engineering, product, and customer-facing teams
  • Low ego, high energy, resilient in a fast-paced environment
  • A strong portfolio showcasing high-quality front-end development work
  • Bonus: prior startup, hacker, or founder experience
  • Eagerness to work in person with us in NYC full time

Benefits

⚕️Comprehensive medical, dental, and vision insurance

🏦 Flexible Spending Account (FSA), Health Savings Account (HSA)

🦮 Expert Healthcare Guidance

💵 Retirement savings

🎄 Company holidays each year

🏖️ Unlimited days for personal time each year

🚌 Flex Commuter Benefits

🥤Office is fully-stocked with drinks and snacks to fuel your work day.

🍽️ Staying late? Dinner is on us

Technology

Customers typically use Shaped as follows:

  1. Connect your data stack, e.g. data warehouse, database or analytics applications
  2. Define your engine. This includes your optimization objective (e.g. clicks vs purchases vs shares), item and user catalogs, feature types and model types.
  3. Consume your results from our real-time, scalable ranking endpoints
  4. Evaluate uplift and model results on our dashboard.

To power all of this, under the hood, we've built a multi-tenanted, real-time machine learning architecture which automatically sets-up and ingests data both in real-time and batch, transforms data and stores it into our proprietary feature/vector store. Ranking models are continuously optimized and fine-tuned based on real-time feedback ensuring customers are seeing the most relevant and up-to-date results possible.

From a machine-learning perspective we use state-of-the-art large scale neural encoding models to understand multi-modal data types such as image, text, audio and tabular data. We provide an exhaustive library of retrieval, ranking and ordering algorithms which are selected based on the specified model definition.

We use both AWS and GCP for cloud. Kubernetes for serverless infrastructure. Python, Javascript and Rust for languages.

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