Senior Software Engineer (Python)
About The Position
Join a team building cloud-native systems, high-throughput data applications, and an expanding set of AI-driven and agentic tooling. This role involves building scalable, high-complexity solutions that power near-real-time decision engines, designing and growing distributed systems including microservices, REST-based APIs, event-driven and streaming pipelines, and mixed relational/NoSQL data storage strategies. The engineer will work closely with architects and other teams to shape and refine system design, make independent architectural calls, and develop backend services and data pipelines in Python, with user-facing features in React. The role also includes building and running cloud-native applications on Azure using Kubernetes, creating data workflows with Airflow or comparable tools, and working with modern data platforms like MongoDB and Snowflake. A key aspect is taking full ownership of services and codebases, applying rigorous testing practices, and using AI development tools to improve output quality. The position supports the build-out of agentic and intelligent automation features, collaborates with data scientists to move models into production, and brings statistical or data-science thinking to system improvements. Strong teamwork, communication, and mentorship are expected.
Requirements
- 5+ years building and shipping production software
- 5+ years working with Python on backend services
- 5+ years with React or another modern frontend framework
- Experience with cloud-native development (Azure preferred) and Kubernetes
- Hands-on experience with technologies like MongoDB (or similar) and Snowflake (or comparable)
- Experience building data pipelines and workflow orchestration (Airflow or similar)
- Background designing and consuming APIs in distributed systems
- Comfort with CI/CD pipelines and modern DevOps workflows
- A track record of owning complex features or services independently
- Experience with AI-assisted development tools and building intelligent workflows (e.g., Copilot)
- Familiarity with agentic or LLM-based frameworks (LangChain, LangSmith, or similar) and orchestration tooling
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
Nice To Haves
- Experience working alongside data science teams on production models
- Background in statistical modeling, experimentation, or data-driven decision-making
- Experience in pricing, logistics, or other high-scale transactional environments
- Strong communication skills and the ability to influence technical and product direction
- Experience mentoring engineers and supporting team growth
- Familiarity with monitoring tools like DataDog, Prometheus, or Grafana
Responsibilities
- Build scalable, high-complexity solutions that power near-real-time decision engines
- Help design and grow distributed systems, including: Microservices and REST-based APIs, Event-driven and streaming pipelines, Mixed relational/NoSQL data storage strategies
- Work closely with architects and other teams to shape and refine system design
- Make independent architectural calls, weighing scalability, reliability, performance, and cost
- Develop backend services and data pipelines in Python, and user-facing features in React
- Build and run cloud-native applications on Azure using Kubernetes
- Create data workflows with Airflow or comparable DAG-based orchestration tools
- Work with modern data platforms such as MongoDB (or similar NoSQL databases) and Snowflake (or comparable analytics platforms)
- Take full ownership of services and codebases — reliability, scalability, and long-term maintainability included
- Break large projects into manageable pieces, help estimate timelines, and flag delivery risks early
- Apply rigorous testing practices (unit, integration, end-to-end) and hold code to a high bar
- Use AI development tools (like GitHub Copilot) to work faster and improve output quality
- Support the build-out of agentic and intelligent automation features
- Team up with data scientists and analysts to move models into production and support experimentation
- Bring statistical or data-science thinking to bear on system improvements where useful
- Build strong working relationships across engineering, product, data, and architecture
- Lead and participate in design discussions and code reviews
- Mentor other engineers and help raise the bar for the team
- Communicate clearly on status, risk, and technical tradeoffs
- Help plan, prioritize, and drive delivery for the team
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What This Job Offers
Job Type
Full-time
Career Level
Senior
