Role OverviewWe 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.