Quanta Credit Services, Inc. is a high-growth company specializing in digital collections solutions. They are seeking a Senior Full Stack Engineer to build and scale their application stack, focusing on backend services, event-driven workflows, and modern web applications while contributing to AI-backed product development.
Responsibilities:
- Build, maintain, and improve services across our application stack:
- AWS Lambda functions, API services, and event-driven workflows
- Batch jobs / scheduled processing and asynchronous pipelines
- Kafka producers/consumers and message-driven architectures
- Workloads running on EC2 / ECS
- SQL-based business logic and data integrations
- Develop and maintain modern front-end experiences in React/Preact (TypeScript)
- Support and extend AI-backed internal/external products
- Improve orchestration, guardrails, observability, and quality
- Partner with product and stakeholders to iterate quickly and safely
- Own features end-to-end: design → implementation → testing → deployment → monitoring
- Improve system quality and operational excellence:
- Monitoring/alerting, dashboards, tracing/logging
- Performance tuning, cost optimization, reliability improvements
- Contribute to architecture decisions and set engineering standards (patterns, libraries, tooling)
Requirements:
- Strong backend engineering experience with Python and/or Node.js (TypeScript) in production environments
- Strong front-end experience with React or Preact (TypeScript) and modern UI patterns
- Solid understanding of SQL and data modeling for application use cases
- Practical experience building on AWS (serverless and container/VM-based)
- Comfort working across the stack — you can move between backend, frontend, and data logic without getting blocked
- Strong ownership mindset: you care about uptime, correctness, maintainability, and customer impact
- Ability to communicate clearly with both technical and non-technical partners
- Snowflake experience (querying, modeling, cost/performance awareness)
- Kafka experience in production (schema evolution, retries, DLQs, ordering semantics)
- Experience with distributed systems patterns (idempotency, at-least-once delivery)
- DevOps/infra familiarity (IaC such as Terraform/CloudFormation/CDK, CI/CD pipelines)
- Experience building/operating AI-enabled product features (evaluation, prompt/versioning, guardrails)