About the Role
We are hiring a Staff Engineer to own the architecture, delivery, and long-term operation of high-impact backend systems. This role sits at the intersection of backend engineering and product analytics infrastructure; equally responsible for the reliability of production systems and the trustworthiness of the data those systems generate.
You will set technical direction, define engineering standards, and lead 1–3 engineers while staying hands-on in the codebase. The ideal candidate has shipped backend systems at scale for consumer or product-led companies and has also owned analytics infrastructure; from event taxonomy and data governance to experimentation and attribution tooling.
Success in the first 3–6 months looks like:
Conduct a clear-eyed audit of existing backend systems and analytics infrastructure, identifying the highest-priority gaps
Establish or improve engineering standards, automated testing processes, and KPI tracking across reliability, data quality, and development speed
Take ownership of analytics infrastructure — cleaning up event taxonomy, ensuring reconciliation across tools, and making data trustworthy for the broader team
Set technical direction for at least one meaningful backend or data initiative and see it through to production
Build a strong working relationship with product and engineering stakeholders through clear, proactive communication
Key Responsibilities
Own the delivery and long-term operation of high-impact backend systems, from architecture to production
Set and evolve backend engineering standards, processes, and technical best practices
Define and actively use KPIs covering system reliability, development speed, data quality, and error rates
Make system-level architectural decisions and clearly communicate tradeoffs to engineering and product stakeholders
Own analytics infrastructure — event taxonomy, governance, and reconciliation across tools like Amplitude and Appsflyer
Ship and maintain experimentation infrastructure including A/B testing, variant assignment, SRM detection, and success metric definition
Debug and maintain user and identity systems across login, logout, multi-device, and reinstall scenarios
Establish automated testing and validation processes that reduce regressions and operational risk
Introduce AI-assisted development workflows where they add leverage, with strong validation and safety mechanisms
Lead and upskill 1–3 engineers, setting technical direction and building engineering capability across the team
Requirements
5+ years building and maintaining backend systems on AWS
Demonstrated experience delivering high-impact backend projects that operate successfully in production
Strong experience building backend services for mobile applications (iOS and Android)
Owned analytics infrastructure at a consumer or product-led company — has taken tools like Amplitude, Mixpanel, or Segment from messy to trustworthy
Experience with RevenueCat or similar subscription tools and Appsflyer or similar attribution platforms
Has shipped experimentation infrastructure including A/B test data quality, variant assignment, and SRM detection
Backend engineering depth on user and identity systems in Python or Node.js production environments
SQL-fluent at the modeling level — has designed event schemas or metrics layers that others relied on
Solid experience with Node.js and TypeScript
Experience with Docker and containerized deployments
Strong understanding of RESTful API design and implementation
Has led 1–3 engineers, set technical direction, and upskilled non-data engineers
Strong sense of ownership, strategic thinking, and a solution-first mindset
Preferred Qualifications
Hands-on experience with AI/ML or LLM-based products
Experience with NestJS framework
Python experience, particularly with Apache Airflow or similar ETL tools
Knowledge of Firebase (Authentication, Firestore, Remote Config)
Experience with Infrastructure-as-Code tools such as Pulumi or Terraform
Familiarity with observability tools such as OpenTelemetry or Signoz
Experience with ElasticSearch or similar search technologies
Experience with video streaming technologies (HLS, MediaConvert)
Tech Stack
Backend: Node.js with NestJS and Restify, Python 3.9 for ETL, Apache Airflow, Sequelize ORM
Frontend: Next.js 15, React 18/19, TypeScript, Tailwind CSS
Infrastructure: AWS (ECS Fargate, S3, RDS, ElastiCache, SQS, CloudFront, MediaConvert), Docker, Pulumi, GitHub Actions, Vercel
Data & Storage: MySQL, PostgreSQL, Redis, ElasticSearch, Firebase Firestore, AWS S3, Cloudflare R2
Observability: Signoz with OpenTelemetry, Winston, Slack webhooks
Compensation & Logistics
Fully remote role
Unlimited PTO
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