Role Overview
We are looking for a Software Engineering Manager with strong experience in Python, React Native, GraphQL, PostgreSQL, and AWS. The role involves building scalable cloud-native applications, improving system reliability and performance, handling production support, and leading complex technical initiatives across backend, mobile, and cloud platforms.
Responsibilities
- Lead, mentor, and develop a team of software engineers across backend, mobile, and cloud platforms, fostering a culture of accountability, collaboration, engineering excellence, continuous learning, and attention to detail.
- Own the overall delivery and operational health of services across Python backends, React Native mobile applications, GraphQL APIs, PostgreSQL databases, and AWS cloud infrastructure, ensuring scalability, reliability, performance, and maintainability.
- Drive architecture design and technical strategy for large-scale, distributed systems, ensuring solutions align with business objectives, scalability requirements, security standards, and long-term platform sustainability.
- Conduct architecture and design reviews for new initiatives and existing systems, providing technical guidance and governance to ensure consistency with engineering standards and best practices.
- Partner closely with Product, UX, QA, DevOps, and business stakeholders to drive technical discovery, define solution approaches, assess risks, and secure cross-functional alignment.
- Oversee engineering process adherence across the software development lifecycle, ensuring compliance with established standards for SDLC, change management, testing, deployment, incident management, and release governance.
- Lead production incident management efforts, including escalation handling, root cause analysis (RCA), corrective actions, and continuous improvement initiatives to improve platform stability and reduce recurring issues.
- Drive continuous improvement initiatives focused on system resiliency, automation, operational efficiency, technical debt reduction, engineering productivity, and AI-driven innovation opportunities.
- Champion observability and monitoring best practices using tools such as Datadog to improve system visibility, alerting, operational insights, and platform reliability.
- Ensure adherence to security, regulatory, compliance, and operational standards across application development, infrastructure management, and production support activities.
- Support hiring, performance management, career development, and succession planning activities for the engineering organization.
- Communicate effectively with technical and non-technical stakeholders through strong verbal and written communication skills.
Requirements
- Python
- React Native
- GraphQL
- PostgreSQL
- AWS
- AWS Lambda
- AWS ECS
- AWS DynamoDB
- AWS S3
- AWS API Gateway
- AWS CloudWatch
- Distributed Systems Architecture
- Cloud-Native Architecture
- Engineering Leadership
- Team Management
- Incident Management
- CI/CD Pipelines
- Observability & Monitoring
- Datadog
- SDLC Process Management
- Root Cause Analysis
- Security & Compliance
- Cross-functional Collaboration
- Technical Communication
Preferred Skills
- AI/ML Technologies
- Automation Tools
- Data-Driven Decision Making
Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
- Proven experience leading and managing software engineering teams delivering production systems using Python, React Native, GraphQL, PostgreSQL, AWS cloud technologies, and distributed architectures.
- Strong experience designing and reviewing scalable cloud-native architectures using AWS services such as Lambda, ECS, DynamoDB, S3, API Gateway, and CloudWatch.
- Experience implementing observability, monitoring, and operational alerting solutions using Datadog or similar platforms.
- Demonstrated experience driving engineering process improvements, operational excellence initiatives, incident management, and release governance practices.
- Strong understanding of CI/CD pipelines, automated testing strategies, observability, system reliability, and modern software development best practices.
- AI-forward mindset with an interest in leveraging AI technologies, automation, and data-driven decision-making to improve engineering efficiency and product innovation.
- Proven ability to lead cross-functional initiatives, manage competing priorities, and communicate effectively with both technical and non-technical stakeholders.
- Strong analytical skills with high attention to detail and a focus on delivering high-quality, scalable solutions.
