• Team: 30 to 50 people across the US and Canada, with main hubs in New York and Toronto
• Funding: Built from 0 to 1 with no external capital (a rare feat for tech startups), then raised one round of funding led by JP Morgan, which fueled significant growth

The Opportunity

We’re seeking a Senior Backend Engineer (Integrations & Platform) to build the backbone our platform runs on. You’ll design scalable backend systems that power complex data integrations with government and enterprise partners, remove manual operational work, and help the team move faster with less friction.

This is a build role and an operate role: when a sync fails or a record looks wrong, you can trace it back to the cause and fix it.

Our integration footprint has grown quickly, and the most demanding piece is a bidirectional data sync with an external partner that requires sophisticated error handling, async workflows, and operational automation. You’ll start there, then turn what you build into the patterns and infrastructure we use for integration reliability across the platform.

This is hands-on, high-impact work where you’ll see results quickly: fewer production issues, faster support resolution, and systems that scale with confidence.

What You’ll Own

• Complex data integrations: Design, build, and maintain deep, bidirectional data integrations with government and enterprise partners, including partners with limited documentation.
• Asynchronous workflows: Build reliable async processing using queues, retries, idempotency, and eventual consistency patterns, handling duplicates, missing dependencies, and validation failures defensively.
• Operational automation: Eliminate categories of manual support work through backend services, Lambda functions, and internal tools that let non-technical teammates diagnose and resolve issues themselves.
• Observability: Implement structured logging, metrics, tracing, and alerting so issues surface before support tickets do.
• Production reliability: Stay close enough to running systems to debug them, including code you did not write.
• Reusable patterns: Establish integration standards the rest of the team can build on.
• Partner collaboration: Work with external vendors on API changes and coordinated deployments.

Your 30/60/90 Day Plan

At FutureFit AI, we value clarity of purpose and rapid momentum. Here’s what success looks like in your first 90 days:

First 30 Days: Learn and Integrate

• Build relationships with the engineering, customer success, and support teams who interact with our integration systems daily
• Deep dive into our most complex integration: the bidirectional sync architecture between our platform and external partners (APIs, data models, async workflows, error patterns)
• Get hands-on with our debugging tools: MongoDB queries for async job tracking, CloudWatch Logs Insights for distributed tracing, SQL queries for data validation
• Ship your first small fixes or improvements: resolve straightforward integration bugs or improve observability in one workflow

Days 31 to 60: Own and Execute

• Take ownership of your first major automation initiative: eliminate a category of manual support work
• Build and deploy backend services and Lambda functions that reduce manual intervention in the integration pipeline
• Implement comprehensive observability (structured logging, metrics, and alerting) so issues surface before support tickets
• Work with the support team to validate that your automation eliminates manual work, and identify the next highest-impact opportunity
• Document runbooks and create internal tools that empower non-technical team members to diagnose and resolve common issues independently
• Collaborate with external partners on any API changes or coordinated deployments your automation needs
• Begin identifying patterns and infrastructure that can be reused across other integrations or platform systems

Days 61 to 90: Lead and Amplify

• Measure and communicate the impact of your automation: reduction in support tickets, decrease in manual intervention time, improvement in data consistency and error rates
• Participate in architectural discussions and planning for other platform initiatives, bringing your expertise in reliability patterns, async workflows, and operational excellence
• Mentor other engineers on the patterns and infrastructure you’ve built, establishing yourself as the go-to person for integration reliability
• Present a technical deep-dive to the broader engineering team on what you’ve learned and built

Required Experience

• 5 to 8+ years of senior-level, hands-on experience in backend, platform, or integration engineering, with a focus on building reliable systems for complex external integrations
• Strong experience with TypeScript and Node.js
• Proven experience building and maintaining complex data integrations at enterprise or government scale (deep data integration work, not only SSO, API configuration, or cloud deployments)
• Strong understanding of asynchronous workloads and processing
• Experience developing reliable, production-grade backend systems
• Strong debugging skills using logs, metrics, and tracing
• Proficiency with at least one SQL or NoSQL database in production
• Comfort working effectively in a fully remote environment

• AWS experience (Lambda, EventBridge, SQS); Azure experience is transferable
• Frontend or full-stack development experience
• Experience with financial, banking, or similarly complex data integrations
• GraphQL API design, MongoDB or DynamoDB for async state management
• Experience with legacy enterprise or government systems
• Multi-tenant architecture experience

Our Tech Stack

• Languages: TypeScript, Node.js
• Architecture: Event-driven (EventBridge, SQS, Lambda)
• Data: MongoDB, PostgreSQL, Redshift
• Observability: CloudWatch Logs Insights
• Infrastructure: AWS, GitHub Actions for CI/CD

Your Education

Your alma mater isn’t our focus. Your grit, hunger, and drive are. If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately, you’re our person.

• Work directly with the founding team
• Unlimited PTO
• Health care
• Career development budget
• Technology reimbursement
• Flexible schedules built on trust

Location

Remote across the US and Canada. We are open to candidates living anywhere in either country, with at least 5 to 6 hours of daily overlap with our EST-based team required. For candidates living in Toronto, our office is conveniently located at 325 Front St West (a short walk from Union Station), and you are welcome to drop by, though it is entirely optional and not a hybrid requirement.

Travel Expectations

Although this role is remote, you may be expected to travel up to once per quarter for off-sites and team gatherings.

Compensation

The base salary range for this role is USD $150,000 to $185,000 for candidates based in the United States and CAD $130,000 to $170,000 for candidates based in Canada, benchmarked to the middle of the market for comparable venture-backed companies. Where you land in the range reflects your applied experience and other criteria established by the hiring committee.

Hiring Journey

At FutureFit AI, our hiring process is designed to help you assess whether this role and our culture are the right fit based on your unique skills, mindset, and experiences. We move fast and work with intensity, so we want you to get a real sense of that from the start.

Each journey includes a mix of interviews and a performance challenge. For this role, that might look like:

• Online Application
• Initial Screen with Talent Acquisition
• Interview with Hiring Manager
• Coding Challenge
• Design Challenge
• 2nd Interview with Head of GTM
• 3rd Interview with CEO
• Final Decision

Generally, this entire process takes around 6 weeks, although the timing can vary due to specific candidate circumstances.

Ready to shape the future of work?

At FutureFit AI, we're not just building a company—we're transforming how talent and opportunity connect. Join our driven team united by a commitment to job seekers and the workforce ecosystems we serve.

• Team: 30-50 across US and Canada (hubs in NYC and Toronto)
• Customers: Workforce development agencies and intermediaries, government agencies, employers
• Industry: SaaS/AI technology
• Funding: Bootstrapped 0-1, then raised funding led by JP Morgan
• Structure: Growth, Customer Success, Product, Engineering, Data, People & Culture, Finance & Operations

Our Core Principles

• Be Curious
• Drive to Outcomes
• Raise the Bar
• Speed Matters
• Own It
• We Over Me

Use of AI in Hiring

At FutureFit, we use artificial intelligence (AI) tools to make our hiring process more efficient, consistent, and equitable—never to replace human judgment. We use AI in the following ways:

• Screening support: AI may help us compare applications against the skills and experience required for a specific role. These skills are defined by the hiring team for each position. A human reviews each application, with the AI assessment as just one input.
• Interview support: In some interviews, we may use an AI notetaker to summarize the discussion so interviewers can focus on being present in the conversation.
• Insights, not decisions: AI provides data points to support our team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people.

© FutureFit AI All rights reserved, we are proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender identity, sexual orientation, age, disability, veteran status, or other applicable legally protected characteristics. We encourage people of different backgrounds, experiences, abilities, and perspectives to apply.