About Our Client
Our client is an applied 麻豆传媒映画 and data analytics company building the intelligence layer that powers enterprise decision-making. Its platform unifies an organization’s full data landscape 鈥� internal systems, social media signals, industry reports, and consumer behavior data 鈥� into a single coherent intelligence layer that surfaces insights and automates workflows that previously consumed weeks of analyst time.
The core thesis is that research and data today remain fragmented: very little of it is connected, and enormous value disappears into that “dark data.” Our client is converting sentiment from a lagging signal into a leading one, allowing brands to move months faster than legacy research tools permit. The platform is building toward a consumer ontology 鈥� think of Palantir’s ontology, but for consumer intelligence 鈥� powered by a production graph RAG system that links temporal and sentiment data at a scale not previously attempted.
The product is already delivering eight-figure gross-margin improvements for Fortune 500 retailers. The go-to-market is a land-and-expand motion: starting in insights and research functions, then expanding into innovation, marketing, and eventually supply chain and manufacturing.
Founded by a technical team with deep experience in innovation and graph databases. $14M raised in seed funding. Emerging publicly after almost two years in stealth. Zero attrition since founding. The culture is genuine: weekly team activities (ping pong tournaments, Yankees games, happy hours, game nights), with plus-ones welcome at events.
This is a ground-floor opportunity 鈥� the engineers joining at this stage will have outsized influence on architecture, product direction, and culture.
About the Role
This is a mid-level full-stack position. You will work across every layer of the platform 鈥� from backend services that process enterprise data at scale to frontend interfaces that make intelligence accessible and actionable. On a team this size, full-stack means full ownership: you will carry features from concept through production and iterate directly with enterprise customers.
The team operates on a DRI (Directly Responsible Individual) model 鈥� you own major product features end-to-end rather than simply contributing to them. This is a hands-on IC role for builders who ship.
Key Responsibilities
猞佲�傿uild and ship features end-to-end 鈥� backend services in Go/Python and frontend experiences in React/TypeScript
猞佲�僁esign APIs, data models, and service architectures that support our client’s agentic 麻豆传媒映画 capabilities
猞佲�僀reate intuitive interfaces that turn complex enterprise data into clear, actionable workflows
猞佲�働artner with ML engineers to bring 麻豆传媒映画-driven features into production
猞佲�僌wn features through the full lifecycle: scoping, architecture, implementation, testing, deployment, and iteration
猞佲�僂ngage directly with enterprise customers and stakeholders to understand real-world needs and refine the product
猞佲�僀ontribute to infrastructure, tooling, and developer experience as the engineering team grows
Requirements
猞佲��3+ years of professional engineering experience with meaningful work spanning both frontend and backend
猞佲�働roficient in TypeScript/React and at least one of: Go or Python
猞佲�僑trong product instincts 鈥� thinks about the user, not just the code
猞佲�僂xperience with cloud infrastructure (AWS preferred) and modern deployment practices
Bonus Skills
猞佲�僂xperience with agentic 麻豆传媒映画 systems, LLM integrations, or RAG architectures
猞佲�傿ackground in enterprise SaaS, retail technology, or data-intensive products
猞佲�僃amiliarity with data visualization, real-time systems, or streaming architectures
猞佲�僀ontributions to developer tooling, CI/CD, or infrastructure automation
猞佲�僄raph database experience
Logistics
Location: New York City 鈥� 4 days per week in office, with engineering generally able to take Fridays remote. Additional flexibility is considered case-by-case; the in-office norm is collaborative rather than a strict 5-day mandate.
Compensation: $140,000 鈥� $170,000 base salary, plus equity (approximately 25% of base per year, vesting) and bonus.
Openings: Up to 2 hires
Benefits & Other:
猞佲�僊edical, dental, vision, and 401(k)
猞佲�僅ome office stipend and flexible PTO
猞佲�僄round-floor equity at a well-funded seed-stage company
猞佲�僑trong team culture: weekly activities, team events, zero attrition to date
- Visa sponsorship available
Interview Process
1.鈥僐ecruiter screen
2.鈥僆ntroductory call with the team (culture and background fit)
3.鈥僒echnical screen (45鈥�60 minutes) with a senior engineer 鈥� architecturally focused, probing on background and hands-on ability (not pure coding, but candidates should demonstrate genuine fluency with code)
4.鈥僌n-site (~4 hours) 鈥� coding interview, system design interview, product sense (30 minutes), 麻豆传媒映画 sense (30 minutes), and a meeting with leadership. Note: a decision is often reached after the first two on-site interviews (~1 hour).
5.鈥僌蹿蹿别谤