Senior Software Engineer

About the Role

We're looking for a Python engineer to join our Business Systems team, which builds and operates the integration layer connecting our core platforms (CRM, payments, and internal services) to the tools our customer-facing teams rely on every day. This is a high-traffic, latency-sensitive environment - our services handle hundreds of thousands of requests a day, and performance directly impacts the people using them in real time.

Why Join Us

You'll own real production performance problems backed by real data - not hypothetical scaling concerns. Our team recently completed a deep, evidence-based incident investigation that traced a latency issue down to specific code-level causes and shipped fixes that measurably cut error rates and response times. If you like solving concrete, high-impact problems and can back your reasoning with data, you'll fit right in.

What You'll Do

• Design, build, and maintain Python services (REST APIs) that integrate our CRM platform with downstream systems like payments, account management, and internal data services
• Diagnose and resolve performance issues in production - including blocking I/O, connection handling, caching strategy, and API latency under load
• Use async Python (asyncio) to safely parallelize I/O-bound work without degrading service throughput
• Implement and tune caching layers (e.g., Redis) for high-throughput endpoints
• Build and maintain integrations with a CRM platform (e.g., Salesforce), including data queries and REST-based sync
• Deploy and operate services in a cloud environment (AWS or similar): serverless functions, containerized services, and monitoring/alerting
• Use observability/APM tooling to trace requests, identify bottlenecks, and validate fixes with real production data
• Write clean, well-tested, maintainable code following solid architectural patterns (clear separation of API, business logic, and infrastructure layers)
• Participate in a rotating on-call/production-support role: triage alerts, coordinate fixes across teams, and help prevent incidents from becoming outages
• Collaborate closely with other engineering teams, DevOps/SRE, and product stakeholders to scope and ship integration work

What We're Looking For

Required:

• Strong professional experience with Python, including async programming and building/maintaining REST APIs
• Solid understanding of data integration between services - how to reliably move, sync, and reconcile data across systems (batch or event-driven), handle failures/retries, and keep data consistent when systems disagree
• Solid understanding of HTTP and API design (pagination, timeouts, rate limiting, caching), and experience debugging performance issues in a live service
• Experience with a key-value or caching data store (Redis experience a plus) and comfort reasoning about caching/invalidation tradeoffs
• Experience with at least one major cloud provider (AWS preferred) - serverless functions, containerized services, or similar
• Comfort reading logs and distributed traces to debug systems issues, not just local code
• Strong written and verbal communication - this team documents root causes and coordinates fixes across other engineering teams

Nice to Have:

• Experience with Twilio (Voice, Studio, Flex, or similar telephony/IVR platforms) - helpful, but we're happy to train a strong Python engineer on this
• Experience integrating with Salesforce (SOQL, Apex, REST APIs)
• Familiarity with an APM/observability platform (e.g., Dynatrace, Datadog, New Relic), including instrumenting services with distributed tracing (e.g., OpenTelemetry) or structured logging
• Comfort writing SQL for debugging and data validation across systems (e.g., data warehouse queries, CRM query languages like SOQL)
• Familiarity with API documentation tooling (OpenAPI/Swagger)
• Experience with AWS Step Functions, container autoscaling, or infrastructure-as-code (Terraform)
• Prior on-call/production-support experience in a fast-moving environment

Base salary range: $140,000-170,000 annually.  Individual pay and level is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.