Lead Engineer - Python

Job Summary

Key Responsibilities

1. AI & Advanced Engineering

• Design and integrate

  AI Agents

  and

  LLM-based workflows

  into production systems.
• Build retrieval pipelines, embeddings, intelligent automation flows, and agent orchestration.
• Work with cloud AI services such as

  AWS Bedrock

  ,

  Azure OpenAI

  , and

  Google Vertex AI

  .
• Implement scalable AI-first backend features using modern AI frameworks.

2. Backend Architecture & Development

• Lead the

  architecture and design

  of enterprise-scale backend systems.
• Build high-quality, reusable, and performance-optimized APIs using

  Django DRF / FastAPI / Flask

  .
• Architect microservices, asynchronous task queues, caching layers, and distributed systems.
• Define coding standards, design patterns, and best practices.

3. Problem Solving & Optimization

• Solve complex backend and system design challenges with strong algorithmic thinking.
• Perform performance tuning, profiling, monitoring, and stability hardening.
• Implement observability, fault tolerance, and reliability patterns across services.

4. Collaboration & Leadership

• Mentor junior and mid-level engineers; conduct reviews and guide technical decisions.
• Collaborate with Product, Frontend, QA, DevOps, and business stakeholders.
• Contribute to sprint planning, estimation, roadmaps, and client technical discussions.
• Ensure delivery of well-planned, scalable, production-ready features.

5. Quality & Delivery

• Write clean, test-driven, maintainable code with unit and integration tests.
• Drive CI/CD pipelines, automated deployments, and release cycles.
• Maintain detailed documentation for system architecture, APIs, and workflows.
• Use

  Swagger / OpenAPI

  for API design and documentation.

Required Qualifications

• 8+ years

  of industry experience building backend systems and APIs in Python.
• Strong expertise with

  Django/DRF

  ,

  FastAPI

  , or

  Flask

  .

• Mandatory:

  Hands-on experience with at least one major cloud provider

• Experience working with or integrating AI Agents / LLM-powered features using:

• Strong knowledge of

  system design

  , distributed systems, concurrency, and async programming.
• Deep experience with relational databases (

  PostgreSQL / MySQL

  ) and familiarity with NoSQL (

  Redis/MongoDB

  ).
• Proven experience architecting microservices, event-driven systems, and scalable backend workflows.
• Solid foundation in

  OOP, DSA, algorithms

  , and clean coding principles.
• Expertise with

  Linux/Unix

  , shell scripting, Git, and API testing tools like Postman.
• Ability to convert complex requirements into scalable, secure backend solutions.
• Excellent communication skills and ability to lead technical discussions across teams.

Nice to Have

• Experience with

  Celery, RabbitMQ, Kafka

  , or event-driven architectures.
• Hands-on experience with vector databases, embeddings, and LLM agent frameworks.
• Familiarity with frontend frameworks (

  React / Angular

  ) for cross-team collaboration.
• Experience with

  Docker, Kubernetes

  , and Infrastructure-as-Code (Terraform/CloudFormation).
• Skills in performance debugging, memory/CPU profiling, and optimization.
• Exposure to CI/CD tools:

  GitHub Actions, GitLab CI, Jenkins

  .
• Knowledge of cloud-native services (e.g.,

  S3, Lambda, API Gateway, Cloud Functions, Azure Functions

  ).