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Inscribe is a fraud detection platform trusted by leading fintechs and banks including Coinbase, Plaid, Bluevine, and Ramp. The company processes millions of applications annually and is backed by top-tier investors including Y Combinator, Threshold Ventures, and Uncork Capital.
As Staff Systems Engineer, you will take ownership of the systems and infrastructure that power Inscribe's real-time API product and internal services. This role blends DevOps, site reliability, cloud architecture, backend engineering, and datastore optimization across the entire stack.
Key responsibilities include:
- Lead design, implementation, and scaling of core infrastructure across compute (ECS), data (Postgres, Redis), observability (Datadog, Grafana), and networking layers
- Optimize deployment pipelines, test environments, and release automation to improve developer efficiency and reduce operational risk
- Monitor and improve production system uptime, latency, and cost performance
- Collaborate with engineers to tune service performance, database access patterns, and caching strategies
- Own capacity planning, system reliability, and on-call best practices — proactively preventing incidents
- Drive architectural decisions for high-throughput API services, balancing scalability with velocity
- Contribute to tooling and processes that foster operational excellence across engineering
- Lead infrastructure projects from roadmap through rollout, anchored in business impact
- Mentor teammates and model high standards for engineering quality, documentation, and decision-making
This is a hands-on role for a high-agency engineer who can evaluate existing systems, identify scalability gaps, and execute improvements aligned with business goals. You'll think in systems, build with urgency, and raise the engineering bar across the company.
Tech stack includes: AWS (ECS, S3, Bedrock), Terraform, Docker, Datadog, Grafana, Postgres, Redis, Python (Django), VueJS, and AI platforms (Anthropic, AWS Bedrock).
REQUIREMENTS:
- 4+ years of hands-on experience in systems engineering, DevOps, SRE, or cloud architecture
- Proven ability to scale production systems and infrastructure in high-growth environments
- Deep familiarity with distributed systems, event-driven architectures, and data-heavy backend systems
- Strong backend development skills in Python with ability to work deep in the codebase
- Passion for reducing toil, automating operational tasks, and improving engineering velocity
- Business-aware mindset: ability to align infrastructure decisions with product goals and growth strategy
- Pragmatic, high-agency problem solver who balances short-term delivery with long-term vision
- Energized by wearing many hats, pushing technical boundaries, and leading by example
