Full-stack Engineer

**Merciv** Full-Stack Software Engineer; $140K – $170K + Equity (~25% of base/yr) + Bonus; New York City (On-site)

**About Company**

Merciv is an applied AI and data analytics company building the intelligence layer for enterprise decision-making. The platform connects an organization's entire data landscape — internal systems, social media trends, industry reports, consumer behavior signals — into a single coherent intelligence layer that surfaces insights and automates workflows that used to take analysts weeks.

The core thesis: research and data are in an outdated state — very little data is connected to one another, and massive value gets lost in that dark data. Merciv is flipping sentiment from a lagging indicator into a leading indicator — enabling brands to make decisions months faster than legacy research tools allow. The platform is building toward a consumer ontology (think: Palantir's ontology, but for consumer intelligence) powered by a production graph RAG system, connecting dots across temporal and sentiment data at a scale unlike anything that's been built.

The platform drives 8-figure improvements in gross margins for Fortune 500 retailers. Land-and-expand strategy: starting in insights/research departments, expanding into innovation, marketing, and ultimately supply chain and manufacturing. Founded by a technical team with deep innovation and graph database backgrounds. Raised $14M in seed funding. Launching publicly after nearly two years in stealth. Zero attrition — no one has left the company. Strong culture: weekly team activities (ping pong tournaments, Yankees games, happy hours, game nights), plus ones welcome at events. This is a ground-floor opportunity — the engineers joining now will have outsized influence on architecture, product direction, and culture.

**About the Role**

This is a mid-level full-stack role. You'll work across every layer of Merciv's platform — from the backend services that process enterprise data at scale to the frontend interfaces that make intelligence accessible and actionable. In a team this size, full-stack means full ownership: you'll take features from idea to production and iterate directly with enterprise clients.

The team uses a DRI (Directly Responsible Individual) model — you own major product features from conception to launch, not just contribute to them. This is a hands-on IC role for builders who ship.

Note: the senior backend pipeline sometimes surfaces candidates who are promising but not fully senior — those candidates may be a fit here if they have strong full-stack breadth. This role is flexible in that regard.

**Responsibilities**

- Build and ship features end-to-end — backend services in Go/Python and frontend experiences in React/TypeScript - Design APIs, data models, and service architectures that support Merciv's agentic AI capabilities - Create intuitive interfaces that translate complex enterprise data into clear, actionable workflows - Collaborate with ML engineers to bring AI-driven features to production - Own features through the full lifecycle: scoping, architecture, implementation, testing, deployment, and iteration - Work directly with enterprise customers and stakeholders to understand real-world needs and refine the product - Contribute to infrastructure, tooling, and developer experience as the engineering team scales

**Required Skills**

A. 3+ years of professional engineering experience with meaningful work across both frontend and backend

B. Proficient in TypeScript/React and at least one of: Go, Python

C. Strong product instincts — thinks about the user, not just the code

D. Experience with cloud infrastructure (AWS preferred) and modern deployment practices

**Bonus Skills**

- Experience with agentic AI systems, LLM integrations, or RAG architectures - Background in enterprise SaaS, retail technology, or data-intensive products - Familiarity with data visualization, real-time systems, or streaming architectures - Contributions to developer tooling, CI/CD, or infrastructure automation - Graph database experience

**Logistical Info**

- Location: New York City - 4 days/week in office, engineering typically takes Fridays flexible/remote. Additional case-by-case flexibility available; in-person culture with understanding, not a hard-and-fast 5-day rule - Compensation: $140,000 – $170,000 base + equity (~25% of salary/yr, vesting) + bonus - Number of openings: Up to 2 (flexible — may absorb strong candidates from backend pipeline who are mid-to-senior but full-stack capable) - **Other:** - Health, dental, vision, 401k - Home office stipend, flexible PTO - Ground-floor equity at a well-funded seed-stage company Strong team culture: weekly activities, team events, zero attrition to date

**Ideal Background**

- Mid-level engineer (3–5 years) at an applied AI startup, verticalized AI company, or high-growth product company. Target companies: Palantir, Cognition, Harvey, Rogo, Cursor, Scale AI, or similar verticalized AI intelligence layers. - Also strong engineers from high-agency product teams at smaller companies or founding engineer types. - Not looking for big-company maintenance roles — want people who've built new things on small teams. - Big tech is okay if they were on a newer product area within a small team, not maintaining legacy systems.

**Green Flags**

- High agency, low ego — technically strong but humble about it, confident without being overconfident - Good communicator — shows up professionally, responsive, articulate about their work - Eager without being desperate — genuinely excited about the opportunity and the tech - Builds things on the side — goes home and codes regardless (personal projects, open source, side builds) - Startup or small team experience — has operated with real ownership, not just task-taking - Excited about applied AI, graph databases, and cutting-edge tech experimentation

**Red Flags**

- Shiny logos without depth — Meta, Google, IBM, OpenAI on resume but was maintaining existing systems, not building new things. Lacks higher-level thinking or agency - Overconfident / high ego — can't balance technical prowess with humility - Poor communicator — slow response times, unprofessional in recruiter calls, can't articulate decisions - Relies heavily on AI tools during technical interviews (major client pain point — seniors should still know their way around code, ask right qualifying questions) - Purely TypeScript without Python experience — client flagged this as a gap for backend-touching roles - Not willing to be in-office in NYC (some flexibility exists, but strict remote-only is a dealbreaker) - Large company background with narrow scope and no evidence of building new things

**Interview Process** - Recruiter screen - Intro call with Rachel or Bapt (culture + background fit) - Technical screen (45–60 min) with senior engineer — architecturally focused, probing on background and hands-on ability (not pure coding, but expect candidates to demonstrate they know their way around code) - On-site (4 hours) — Coding interview, System design interview, Product sense (30 min), AI sense (30 min), Meeting with Bapt + co-founder. Note: decision is often made after the first 2 on-site interviews (~1 hour) - Offer