Engineering Manager

Flipkart · Pune

  • Experience13–14 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted3 Sept 2026
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About Flipkart

Flipkart is hiring in Pune in ecommerce retail. This role looks for around 13+ years of experience.

Skills

  • Java
  • Node.js
  • React.js
  • TypeScript
  • AI / LLM
  • Agentic Systems
  • Python
  • PySpark
  • Big Data ecosystems
  • Hadoop
  • PostgreSQL
  • MySQL
  • Database sharding
  • Query optimisation
  • Large-scale data storage strategies
  • Distributed Systems
  • Messaging
  • Kafka
  • Redis
  • RabbitMQ
  • DevOps
  • Cloud
  • Docker
  • Kubernetes
  • Nginx
  • AWS
  • GCP
  • Microservices architecture
  • Agile
  • Full SDLC processes
  • Functional specifications
  • Architecture documentation
  • Design specifications
  • Unit testing
  • Performance optimisation
  • AI Developer Productivity Tools
  • ChatGPT
  • Cursor
  • System reliability
  • Scalability
  • Observability
  • AI/ML models

The role

An engineering manager at an e-commerce company builds AI-powered enterprise systems and leads backend and frontend engineering with Agentic AI systems, LLM-based solutions, and RAG pipelines. This person applies Big Data ecosystems and microservices architecture to scale production platforms and engineering teams.

Full job description

Requirements:

13+ years of software development experience.

Strong communication, stakeholder management, and presentation skills.

Strong backend and frontend hands-on experience with: Java, Node.js, React.js, TypeScript, AI / LLM and Agentic Systems.

Experience building AI-powered enterprise systems, including: Development of Agentic AI systems, Implementation of LLM-based solutions, and Development of RAG (Retrieval Augmented Generation) pipelines.

Experience with: LangChain, LLaMA, YOLO, Roboflow NeMo.

Experience building production-grade AI models and integrating them into enterprise platforms.

Data Engineering and Big Data: Strong experience with: Python, PySpark, Big Data ecosystems, Hadoop.

Experience building large-scale data processing pipelines and ML data workflows.

Databases: Strong experience with PostgreSQL, MySQL.

Knowledge of: Database sharding, Query optimisation, Large-scale data storage strategies, Distributed Systems and Messaging.

Experience with: Kafka, Redis, RabbitMQ, DevOps and Cloud.

Hands-on experience with: Docker, Kubernetes, Nginx, AWS, GCP, and Development Practices.

Strong experience working with Microservices architecture.

Experience delivering high-scale, production-grade enterprise systems.

Experience with Agile development methodologies.

Familiarity with full SDLC processes, including: Functional specifications, Architecture documentation, Design specifications o Unit testing, Performance optimisation, AI Developer Productivity Tools, Experience leveraging modern development tools such as ChatGPT, Cursor Other AI-assisted development tools.

Experience building AI-driven SaaS platforms.

Prior experience scaling engineering teams and distributed systems.

Strong knowledge of system reliability, scalability, and observability.

Experience integrating AI/ML models into real-time production systems.