Sr. Backend Engineer - Integrations & Platform

Rockstar is recruiting for an innovative, mission-driven AI company focused on the future of work. The client is dedicated to helping more people access better jobs faster and more affordably, with a particular emphasis on removing barriers to opportunity. Their AI-powered platform modernizes workforce development, replacing outdated systems and unlocking human potential at scale. They are a dynamic, high-velocity team motivated by meaningful impact.

Come join the Platform Team!

High velocity, high intensity, high trust, high bar, high impact, and a will to win.

If those words resonate deeply, this could be the next career move. They are seeking someone who leads with humility, pursues audacious goals, and is motivated by meaningful impact on people and the world.

The core mission is to help more people get to better jobs faster and cheaper, with a specific focus on those facing barriers to opportunity. The work helps resolve the growing issue of economic inequality, ensuring that no one is left behind in the future of work. The AI-powered platform brings efficiency and insight to workforce development, replacing outdated systems and unlocking human potential at scale.

Ready to make an impact? Apply today.

Important note: Data shows that men typically apply when meeting 3/10 requirements, while women often wait until it's 10/10. They encourage you to apply if you see a strong (not necessarily perfect) fit.

The company is looking for a Senior Backend Engineer to join the Integrations & Platform team. The successful candidate will play a critical role in building the backbone of the platform. They will design smart, scalable backend systems that power complex integrations with government and enterprise partners, eliminate manual operational work, and set the team up to move faster with less friction.

The initial focus will be on the most technically demanding integration: a bidirectional sync system that requires sophisticated error handling, async workflows, and operational automation. The engineer will build the infrastructure and patterns that not only solve this specific challenge but become the foundation for how the company approaches integration reliability and operational excellence platform-wide.

It is a hands-on, high-impact role where the candidate will see immediate results — fewer production issues, faster support resolution, and systems that scale confidently — while building expertise that positions them to drive platform initiatives across the growing infrastructure.

At the company, they value clarity of purpose and rapid momentum. Here’s what success looks like in the first 90 days:

First 30 Days – Learn and Integrate

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

Days 31–60 – Own and Execute

• Take ownership of the 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 for the automation so issues surface before support tickets
• Work with the support team to validate the 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 (vendor systems) on any API changes or coordinated deployments needed for the automation
• Begin identifying patterns and infrastructure that could be reused across other integrations or platform systems

Days 61–90 – Lead and Amplify

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

Core Technical

• Strong backend development experience with TypeScript/Node.js and modern AWS services (Lambda, EventBridge, SQS)
• Deep understanding of distributed systems patterns: idempotency, retries, eventual consistency, and error handling
• Experience building and maintaining integrations with third-party APIs
• Proficiency with at least one database technology (SQL or NoSQL) for production systems
• Strong debugging and troubleshooting skills using logs, metrics, and tracing

Highly Valuable

• GraphQL API design and implementation
• MongoDB or DynamoDB for managing async workflows and state machines
• SQL/data warehouse experience for validation and analytics (Redshift, PostgreSQL)
• Experience with government APIs, legacy enterprise systems, or partners with limited documentation
• Event-driven architecture at scale using serverless patterns
• CloudWatch Logs Insights, New Relic, or similar observability platforms
• Multi-tenant architecture and tenant-specific configuration managements

• 5–8+ years in backend, platform, or integration engineering roles with focus on building reliable systems for complex external integrations
• Built and maintained bidirectional sync systems between internal platforms and third-party APIs, handling edge cases like duplicate records, missing data dependencies, and validation failures
• Designed and implemented event-driven architectures using serverless technologies (Lambda, Step Functions) for async workflows at scale
• Integrated with legacy or government systems where API documentation is incomplete and error handling must be defensive
• Worked extensively with both SQL and NoSQL databases — using document databases for state management and SQL for data validation and analytics
• Built operational automation and internal tools that reduced manual support work, enabling non-technical teams to self-serve and resolve issues
• Implemented comprehensive observability for integration pipelines: structured logging, metrics, distributed tracing, and alerting for proactive issue detection
• Worked in environments with , compliance requirements, or high operational load where reliability and correctness are non-negotiable
• Collaborated with customer support and success teams to understand pain points, prioritize fixes, and build solutions that reduce escalations
• Experience with multi-tenant architectures and tenant-specific configurations

• Languages: TypeScript, Node.js
• Cloud: AWS (preferred)
• Architectures: Event-driven (e.g., AWS EventBridge, SQS, Lambda, Kafka)
• APIs: Integration with third-party APIs and data automation across systems
• Patterns & Practices: Queueing, retries, idempotency, logging, alerting, observability

The alma mater is not the focus. Grit, hunger, and drive are. If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately—you’re the right person.

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

This role is remote in Canada. For candidates living in Toronto, the office is conveniently located at 325 Front St West (a short walk from Union Station). The team comes in 1-2x a week, usually on Wednesdays. They would love to see you too!

Although this role is remote, you may be expected to travel up to once per quarter.

The base salary range for this role is $130,000 - $170,000 CAD. This range reflects the varying levels of expertise and responsibilities that will be determined through the interview process, based on applied experience and other criteria established by the hiring committee.

The hiring process is designed to help you assess whether this role and the culture are the right fit based on your unique skills, mindset, and experiences. The team moves fast and works with intensity, so they 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 Director of People & Culture
• Interview with Hiring Manager
• Coding Challenge
• Design Challenge
• 2nd Interview with Head of GTM
• 3rd Interview with CEO
• Final DecisionGenerally, this entire process takes around 6 weeks, although the timing can vary due to specific candidate circumstances.

The company is not just building a company—they are transforming how talent and opportunity connect. Join the driven team united by a commitment to job seekers and the workforce ecosystems they 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

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

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

• Screening support: AI may help 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, they 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 the team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people.