Company
Merciv
Annual salary
$120k – $200k/yr
Location
New York, NY
Listed
176d ago
- Experience:
- 3+ years
- Workplace:
- 4-5 days in-office in Soho, New York
- Visa:
- Visa sponsorship not available
- Equity:
- Competitive equity
On-site in New York, NY. Visa sponsorship not available.
Send us your LinkedIn and CV. If your experience fits, we'll introduce you to the recruiter filling this role.
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About this Role
As a Full Stack Engineer, 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 that 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 our enterprise clients.
This role is ideal for engineers who are energized by breadth, who want to understand the whole system, and who see product context as a superpower rather than a distraction.
What you'll do
- 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
What you need
- 3+ years of professional engineering experience with meaningful work across both frontend and backend
- Proficient in TypeScript/React and at least one of these languages: Go, Python
- Strong product instincts (you think about the user, not just the code)
- Comfortable with ambiguity and rapid iteration; you can take a vague problem and turn it into a shipped feature
- Experience with cloud infrastructure (AWS preferred) and modern deployment practices
- Adaptable to evolving workflows and tools, using AI and agentic tools to improve processes.
- You care about quality but optimize for impact (you know when to polish and when to ship)
Bonus
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
Frequently Asked Questions
How do I apply for the Software Engineer (US) role at Merciv? +
Use the Apply for a referral button on this page to send us your LinkedIn and CV. If your experience fits, we'll introduce you to the recruiter filling this role. They'll email you to check you're interested, then put you forward for this job or others that suit you better. It's free.
What does this Merciv role pay? +
The listing gives $120k – $200k/yr.
Is this role remote? +
The listing gives the location as New York, NY. 4-5 days in-office in Soho, New York. Visa sponsorship not available.
Interview Prep
Sample questions for a Software Engineer role, written in-house to help you prepare.
How do you approach designing a system when the requirements are still likely to change?
I design around the parts of the problem I'm confident are stable, like the core data model, and keep the parts most likely to change, like specific business rules, isolated behind clear interfaces. Over-engineering flexibility everywhere just adds complexity to parts of the system that were never going to change.
What's your process for debugging an issue that only reproduces in production, not locally?
I add targeted logging around the suspected area and compare production data or configuration against my local setup, since an issue that's environment-specific usually traces back to a real difference between the two rather than a fundamentally different bug. I avoid making speculative changes without first confirming where the divergence is.
How do you decide when a piece of code needs a test versus when it's low-risk enough to skip?
I prioritize tests for logic with real business consequences if it breaks, or code that's likely to be touched again later by someone unfamiliar with it. Simple, rarely-changed glue code gets less coverage, since the cost of a thorough test there often exceeds the risk it's protecting against.
How do you evaluate a proposed technical solution's trade-offs, like performance versus maintainability?
I start from the actual constraint that matters for this specific system, whether that's genuinely performance-critical or whether maintainability is the bigger long-term cost, rather than defaulting to whichever trade-off I personally prefer. Optimizing for performance the system doesn't need just adds complexity nobody benefits from.
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