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Python Developer Lead

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Onsite

Python Developer Lead

Amiseq

Python Developer Lead

Skills

DockerReactDjangoFlaskPythonJavaMicroservicesPostgreSQLGraphQLGitLabJenkinsSwagger/OpenAPICypressAIAWSGitHubKubernetesJiraFastAPIKanbanComplianceTerraformAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Onsite

Published on:

13 August 2026

What they need


Lead Python Developer

Amiseq Chennai (Navalur)
Full-time - 7 - 12 Years Experience
Education: BE CS, MCA, M.Sc. CS, M.Sc./B. Tech IT (4+ years technical education)

Up to Rs. 18 Lakhs per annum (based on experience & skills)

Role Overview

As a Lead Python Developer, you will serve as the primary technical driver for a high-performance engineering pod. This is a "Player-Coach" rolebalancing deep technical execution (hands-on coding, system design, and architecture) with the mentorship of developers. You will oversee the full software development lifecycle, from UI component architecture to DevOps automation and cloud deployment, ensuring the delivery of scalable, robust web applications.

Key Responsibilities

1. Full-Stack Architecture & Development

  • Frontend Excellence: Lead the development of responsive, high-performance user interfaces using React.js or Angular. Champion component reusability and enforce state management best practices (Redux, Context API, RxJS).
  • Python Backend Mastery: Design, build, and maintain scalable server-side logic using frameworks such as FastAPI, Django, or Flask.
  • Design Ownership: Create and maintain Low-Level Designs (LLD), including API contracts (Swagger/OpenAPI), database schemas, and frontend component hierarchies.
  • PoC & Prototyping: Rapidly build Proof of Concepts to validate new features, UI/UX flows, or third-party integrations.

2. DevOps & Automation

  • CI/CD Integration: Drive the automation of builds and deployments using GitHub Actions, Jenkins, or GitLab CI.
  • Containerization: Ensure all services are containerized using Docker and orchestrated via Kubernetes (AKS/EKS).
  • Infrastructure as Code: Manage cloud-native environments using Terraform or CloudFormation.

3. AI & Specialized Automation

  • AI-Enabled Features: Implement Python-based integration for AI services (OpenAI SDKs, LangChain) into the application layer.
  • Process Automation: Use Python for scripting and task automation to improve internal team velocity and system reliability.

4. Technical Leadership & Agile

  • Code Mentorship: Conduct deep-dive code reviews to ensure compliance with LLD and high-quality standards.
  • Sprint Management: Lead Story Point estimation and Sprint Planning. Translate complex business requirements into clear technical tasks for the team.

Required Skills & Experience

Technical Requirements:

  • Experience: 6-12 years in Software Engineering; 2+ years leading technical teams.
  • Primary Stack: Expert-level Python (FastAPI, Django, or Flask). Optional: Dotnet Core / Java.
  • Frontend Frameworks: Strong proficiency in React.js or Angular (v12+).
  • Database & API: Experience with PostgreSQL/NoSQL and designing RESTful or GraphQL APIs.
  • Cloud & DevOps: Hands-on experience with AWS or Azure and Docker/K8s.
  • Agile Mastery: Expert in Scrum/Kanban, Story Pointing, and Jira-based workflows.
  • AI/Automation: Foundational knowledge of LLMs (RAG, Prompting) and experience with Python-based automation.
  • System Design: Strong grasp of Design Patterns, Microservices architecture, and API-first design.

Added Benefits (Preferred)

  • Security: Familiarity with OAuth2, JWT, and OpenID Connect.
  • Testing: Experience with Unit Testing (PyTest) and Frontend Testing (Jest/Cypress).
  • AI Tooling: Basic experience with Vector Databases (Pinecone/Milvus) or prompt engineering.

Soft Skills

  • Mentorship: Ability to mentor junior developers and foster a culture of technical excellence.
  • Communication: Strong communication skills to present technical roadmaps to stakeholders.
  • Conflict Resolution: Skills to keep the engineering pod aligned during high-pressure delivery cycles.
  • Problem-Solving: Strong programming foundations and design principles with minimal dependency on AI tools.

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