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Simfluent

Software Engineering Manager

Posted Updated
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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.

Skills

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See also

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