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Mean Stack Remote Jobs in New York (NOW HIRING)

Enterprise Account Manager

New York, NY · On-site +1

$150K - $200K/yr

Please note this role is based on-site at our Brooklyn Navy Yard office with Remote Wednesdays. We ... We know that if it isn't a good fit at the moment, it doesn't necessarily mean that it won't be a ...

Architect and ship full-stack features end-to-end, from scoping and technical design through build ... Office & Remote Setup * Up to $750 one-time home office or desk setup stipend for NYC-based ...

Enterprise Account Manager

New York, NY · On-site +1

$150K - $200K/yr

Please note this role is based on-site at our Brooklyn Navy Yard office with Remote Wednesdays. We ... We know that if it isn't a good fit at the moment, it doesn't necessarily mean that it won't be a ...

Mean Stack Remote information

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How much do mean stack remote jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for mean stack remote in New York is $64.83, according to ZipRecruiter salary data. Most workers in this role earn between $53.89 and $74.71 per hour, depending on experience, location, and employer.

What are some common challenges faced by Mean Stack developers working remotely, and how can they be overcome?

Mean Stack developers working remotely often face challenges such as collaborating across different time zones, troubleshooting complex technical issues without immediate in-person support, and maintaining focus in a home environment. These can be overcome through regular participation in team meetings, proactive communication using collaboration tools like Slack or Microsoft Teams, and establishing a dedicated workspace to minimize distractions. Leveraging online communities and comprehensive documentation can also help solve technical problems more efficiently. Staying organized and aligned with team goals ensures productivity and smooth project delivery, even when working remotely.

What is a Mean Stack Remote?

A MEAN Stack Remote job involves developing web applications using the MEAN (MongoDB, Express.js, Angular, and Node.js) stack while working remotely. Developers in this role build and maintain full-stack applications, handling both front-end and back-end tasks. They collaborate with teams using online communication tools and version control systems. This job requires expertise in JavaScript, database management, API integration, and cloud deployment. Remote MEAN stack developers must be self-motivated and proficient in problem-solving to work independently.

What are the key skills and qualifications needed to thrive in a Mean Stack Remote position, and why are they important?

To thrive as a Mean Stack Remote developer, you need expertise in JavaScript-based technologies such as MongoDB, Express.js, Angular, and Node.js, as well as a solid understanding of RESTful API design and database management. Familiarity with source control systems like Git, cloud services (e.g., AWS or Azure), and agile development tools is typically required, and certifications in web development can be advantageous. Standout soft skills include strong self-motivation, effective communication, problem-solving abilities, and the discipline to manage time independently in a remote setting. These skills are essential to building scalable, high-quality applications, collaborating effectively with distributed teams, and meeting project deadlines in a fully remote environment.

What cities in New York are hiring for Mean Stack Remote jobs? Cities in New York with the most Mean Stack Remote job openings:

Enterprise Account Executive

Polar Analytics

New York, NY • Remote

Full-time

Re-posted 2 days ago


Job description

Who we are

Polar is the complete data platform for omnichannel commerce. We connect every data source a brand runs on - Shopify, Amazon, NetSuite, Meta, Google, Klaviyo - into a single Snowflake warehouse, layer a commerce semantic layer on top, then add AI so operators can ask questions, get answers, and automate workflows without writing SQL.

Our founders came from Turo and Airbnb in Silicon Valley. They built data platforms at scale and wanted to bring that level of sophistication to fast-growing commerce brands. We support 4,000+ merchants, and zero direct competition with a better solution. We serve brands like Quadlock, gorjana, Joseph Joseph, and ARMRA Colostrum.

We shipped MCP integrations with Claude and ChatGPT, AI automations, and an AI Data Engineer that builds connectors on demand. Our positioning: the data layer to build agent workflows for commerce. Customers tell us things like "this is a dream come true - it feels like the first time they showed me Shopify".

How we operate


We publish our operating principles internally and we mean every word. Here are the ones that matter most if you're thinking about joining:

Customer Obsession. Every decision starts with: does this make our users' lives better? If the answer isn't clear, go talk to a customer before you build anything.

Own the Number. Every metric has an owner. If it's yours, know it cold - the trend, the why, the plan. Don't wait for someone to ask. If it's off track, you should be the first to say so.

Raise the Pace. Always ask: what would it take to do this in half the time? Speed is our edge. We try 100 things while the competitor tries one.

Don't Fail Silently. If it's broken, say it. If you're stuck, raise your hand. Hiding problems is the one thing that will actually get you in trouble.

Here to Win, Not to Be Right. Quiet ego, loud standards. Don't fight to be right - fight to win together. Be ruthless on quality, never rude about it.

Optimize for Polar, Not Your Function. "Not my scope" doesn't exist here. If it makes us win, it's your scope.

We're a remote-first team that runs daily standups, ships weekly, and holds ourselves to a standard most companies talk about but don't enforce. We're transitioning from founder-led intensity to systematic company intensity - which means we need people who can maintain the pace autonomously, not just when someone's watching.


Why this role exists

We're closing enterprise deals already. Q1 2026 was a company record. The unit economics are strong: $40k ACV, <30 days close time on qualified deals, 40% win rate.

But enterprise deals are getting more complex. They require executive stakeholder mapping, build vs buy positioning against internal data teams, and longer cycles with multiple decision-makers. We need someone who can run these deals end-to-end - from first call to close - with the technical credibility and deal orchestration skills that enterprise requires.

You'll work alongside our Head of Sales and partner closely with our partnerships team. The opportunity is massive and the foundation is built - we need someone who can close at the next level.

What you'll own
  • Full-cycle enterprise deals from discovery through close. Your targets will be mid-market and enterprise DTC brands doing $50M-$500M+ GMV with complex omnichannel operations

  • Executive stakeholder mapping and multi-threaded selling across ecommerce, marketing, data, and finance teams. You'll navigate deals where the CRO, VP of Ecommerce, and CFO all need to sign off

  • Build vs buy conversations with technical stakeholders. Brands with data teams are evaluating building their own stack - you need to credibly position why 8 separate tools and a 6-12 month project isn't the answer. Your talk track branches based on team size and sophistication

  • Pipeline generation in partnership with our SDR function, partnerships team, and your own outbound. You'll own the number and know it cold - the trend, the why, the plan

  • AI and MCP demos that land. Our AI roadmap - semantic layer, AI data analyst, AI strategist, autonomous agents - is the strongest part of our pitch for enterprise. You need to demo MCP on Claude and ChatGPT live and explain the four-level AI journey confidently

  • Consultative discovery using our structured playbook. We've built discovery frameworks for goals, stack, pain/product, and decision process - you'll master them and make them your own

  • Deal forecasting and pipeline hygiene. No silent slips - if something is off, say it now. Reforecast early with a new plan, don't wait for it to blow up

Who you are

We don't have a rigid checklist of requirements. We're looking for a specific kind of person:

  • You've spent 3-5 years closing $50k+ enterprise SaaS deals with technical evaluation processes. You've sold to multi-stakeholder buying committees, not just single-threaded to one champion

  • You're technically credible. You can discuss semantic layers, Snowflake instances, attribution models, and data architecture without sounding like you're reading a script. CTOs and data leads take you seriously

  • You have experience selling to ecommerce, retail, or DTC brands - or you've sold data/analytics/BI tools and can learn the vertical fast

  • You're a consultative seller who positions as a strategic advisor, not a vendor. You help prospects understand their data architecture gaps and business impact before you pitch features

  • You're patient with long cycles but relentless on next steps. Enterprise deals require relationship building across multiple stakeholders - you know how to keep momentum without being pushy

  • You're comfortable demoing AI products live and excited about the space. This isn't a "hand it to the SE" role - you run your own demos

  • You communicate clearly and concisely. No fluff, no jargon. You close the loop on everything

What separates A-players

You run discovery like a consultant, not a checklist. You map every stakeholder in the first two calls and know exactly who the economic buyer is. You can pivot between talking ROAS with a Head of Growth and data architecture with a CTO in the same meeting. You build pipeline when you're ahead of quota, not just when you're behind. And you treat forecasting as a craft - your commits are accurate because you understand your deals, not because you're sandbagging.

What our customers see

These are the kinds of results you'll sell against:

  • Thiege consolidated 9 different tools into Polar and saved $300K per year vs building their own data stack

  • CABA improved their ROAS by 65% using our attribution model and incrementality testing to reallocate spend

  • Modular Closet grew Klaviyo flow revenue by 50% with our CDP and identity resolution layer

  • Quadlock started with us below $10M - we helped them scale to 9 figures and a $350M acquisition

How we hire

We believe the best people want to go through a demanding process. We've learned the hard way that great interviewers aren't always great operators - so our process is designed to see how you think, not how you present.

1. Motivation screen - A quick call to understand what drives you and whether there's mutual fit


2. Live case study - A real scenario where you work through a problem in real time. No prep decks, no take-homes. We want to see how you actually operate


3. Leadership conversations - Meet the team, understand the culture, make sure this is somewhere you want to build


Our hiring bar: if this person started a company, would we want to join them?