Manager, Software Engineering (Python)

Position Overview

As an Engineering Manager, you will lead a team of software engineers in building scalable, reliable, and efficient web applications and microservices in the for “News and Competitive Data Analysis Platform”. You will drive technical excellence, system architecture, and best practices while fostering a high-performance engineering culture. You’ll be responsible for managing engineering execution, mentoring engineers, and ensuring the timely delivery of high-quality solutions. 

Your expertise in Python , Django, React, Apache Solr, RabbitMQ, and Postges and other NoSQL cloud databases will help shape the technical strategy of our SaaS platform. You will collaborate closely with Product, Design, and DevOps teams to align engineering efforts with business goals. 

Key Responsibilities:

• Lead the design and development of internal platforms that empower product teams to build, deploy, and scale services seamlessly.
• Integrate AI/ML capabilities into platform tools—such as semantic search, intelligent alerting, auto-scaling, and workflow automation.
• Optimize distributed backend systems (using Celery, RabbitMQ) for efficiency, reliability, and performance across tasks like crawling, processing, and notifications.
• Collaborate closely with DevOps, SRE, data, and ML teams to build secure, observable, and scalable infrastructure across AWS and GCP.
• Drive cloud modernization, including the strategic migration from GCP to AWS, standardizing on containerization and CI/CD best practices.
• Foster a culture of platform ownership, engineering excellence, and continuous improvement across tooling, monitoring, and reliability.
• Mentor engineers, enabling them to grow technically while influencing platform architecture and cross-team impact.

• 8+ years of experience in backend or platform engineering, with 2+ years in a technical leadership role.
• Strong hands-on experience with Python (Django, Celery), React, and building scalable distributed systems.
• Deep knowledge of message brokers (RabbitMQ), PostgreSQL, and search technologies like Apache Solr or Elasticsearch.
• Exposure to AI/ML technologies—such as NLP, semantic search, LLMs, or vector databases (e.g., FAISS, Pinecone).
• Experience with CI/CD pipelines, container orchestration (Docker, Kubernetes), and observability tools.
• Proven ability to lead cloud migration initiatives and manage infrastructure across AWS/GCP.
• A platform-first mindset—focused on developer productivity, reusability, scalability, and system performance.