Senior Software Engineer

About the role

This role targets a Python engineer within the Business Systems team. Production services handle high traffic and low latency, and the team owns the integration layer connecting core platforms to customer-facing tools.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

What you'll do

Production latency and blocking I/O issues are diagnosed and resolved by analyzing data and tracing requests to specific code-level causes.

Caching layers, such as Redis, are implemented and tuned to support high-throughput endpoints.

Serverless functions, containerized services, and monitoring or alerting are deployed and operated on cloud infrastructure such as AWS.

Requests are traced, bottlenecks are identified, and fixes are validated using observability/APM tooling and real production data.

Requirements

Strong professional experience with Python, including async programming and building or maintaining REST APIs is required.

Data integration between services is understood deeply, including reliable sync, failure handling and retries, and consistency when systems disagree.

HTTP and API design skills are solid, including pagination, timeouts, rate limiting, and caching strategies, with experience debugging performance issues in a live service.

Experience with a key-value or caching data store, such as Redis, and comfort with caching and invalidation tradeoffs is expected.

Experience with at least one major cloud provider, such as AWS, using serverless functions, containerized services, or similar services is required.

Logs and distributed traces are used to debug systems issues, not only local code inspection.

Written and verbal communication is strong to document root causes and coordinate fixes across other engineering teams.

Nice to have

Experience with Twilio platforms, such as Voice, Studio, or Flex, is helpful, but training is provided for strong Python engineers.

Salesforce integration experience using SOQL and REST APIs is a plus.

Familiarity with an APM/observability platform, such as Dynatrace, Datadog, or New Relic, including instrumenting services with distributed tracing or structured logging, is valued.

Comfort writing SQL for debugging and data validation across systems, such as data warehouse queries or CRM query languages, is a plus.

Knowledge of API documentation tools like OpenAPI or Swagger is a plus.

Understanding of AWS Step Functions, container autoscaling, or infrastructure-as-code tools such as Terraform is a plus.

Prior on-call experience in fast-moving environments is a plus.

Practical notes

Citizenship or Green Card status. Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

Engineers build and maintain integration layers that connect systems.

The role relies on async programming and caching to manage latency and throughput.

Observability tools guide decisions in production troubleshooting.

Ownership of production issues is central to the work.

Collaboration across engineering and product teams drives integration delivery.