Senior Software Engineer (Python and React Native)

Job Responsibilities:

Own the end-to-end health, scalability, and performance of services across Python backends, React Native mobile applications, GraphQL APIs, PostgreSQL databases, and AWS cloud infrastructure.
Lead and direct large-scale, complex, cross-functional initiatives, translating business requirements into scalable technical solutions and driving execution from design through delivery.
Architect and implement distributed systems using AWS services (e.g., Lambda, ECS, DynamoDB, S3, API Gateway, CloudWatch) with a focus on reliability, observability, performance, and cost optimization.
Design, develop, and optimize scalable backend services and APIs using GraphQL and PostgreSQL, ensuring high availability, data integrity, and maintainability.
Drive the discovery phase of major initiatives, partnering with Product, UX, and business stakeholders to define high-level designs, validate solutions through proofs of concept and prototypes, and secure cross-functional alignment.
Take full ownership of production issues, leading incident response, root cause analysis (RCA), and permanent fixes, while improving system resilience to prevent recurrence.
Serve as a technical escalation point, diagnosing complex issues across mobile, backend, and cloud systems, guiding teams through resolution, and ensuring clear communication with stakeholders.
Elevate engineering quality by designing and enforcing comprehensive QA strategies, including automated unit, integration, and end-to-end testing for React Native applications and backend services within CI/CD pipelines.
Review and guide mobile and backend system design, code quality, and test coverage, ensuring alignment with best practices in scalability, security, performance, and maintainability.
Lead on-call and incident management practices, including improving monitoring, alerting, runbooks, and post-incident reviews to reduce MTTR and incident frequency.
Monitor system and application performance proactively using observability and monitoring platforms such as Datadog, leveraging logging, metrics, tracing, and alerting to identify and resolve bottlenecks.
Drive continuous improvement initiatives by identifying and implementing enhancements, refactoring opportunities, automation strategies, and technical debt reduction initiatives across mobile and cloud platforms.
Contribute AI-forward thinking and innovation by identifying opportunities to leverage AI-assisted development, automation, operational intelligence, and data-driven engineering practices.
Maintain and evolve technical documentation, including mobile architecture, API contracts, infrastructure configurations, operational playbooks, and support procedures.
Ensure adherence to security, regulatory, and compliance standards, embedding best practices into both mobile and backend development workflows.
Lead and support mobile releases, backend deployments, and infrastructure changes, ensuring minimal disruption and alignment with change management processes.
Mentor engineers and provide technical leadership, fostering a culture of engineering excellence, ownership, collaboration, and continuous learning.

Basic Qualifications:

Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
Proven experience building and operating production systems using Python, React Native, GraphQL, PostgreSQL, and AWS cloud technologies, with a strong focus on reliability, scalability, and quality.
Strong experience designing and supporting distributed cloud-native architectures using AWS services such as Lambda, ECS, DynamoDB, S3, API Gateway, and CloudWatch.
Experience implementing observability, monitoring, and alerting solutions using Datadog or similar platforms.
Strong understanding of CI/CD pipelines, automated testing strategies, system reliability, observability, and modern software engineering best practices.
Experience troubleshooting and resolving complex production incidents across backend, mobile, and cloud platforms.
AI-forward mindset with interest or experience in leveraging AI technologies, automation, and intelligent tooling to improve engineering efficiency and product innovation.
Excellent verbal and written communication skills, with the ability to collaborate effectively across technical and non-technical teams.
Strong analytical and problem-solving skills with high attention to detail