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Lead Software Engineer - PythonClarivate · IND - Bangalore (DRG)
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Clarivate

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Lead Software Engineer - Python

🗓️ Posted 2026-09-30 IND - Bangalore (DRG) Full-time Hybrid ICT
💰 Salary Not shared 📊 Market 200,000 GBP–350,000 GBP/mo

About the Company

We build the backend that powers every AI feature in the company. From the models in production to the AI tools people use day to day, it all runs through systems our team owns and maintains. It's a role with real reach; the work you do here shows up across the whole company.

Requirements

  • ● Minimum 6+ years of backend (Python) or full-stack software engineering experience
  • ● Strong experience with FastAPI
  • ● Hands on experience of SQL and relational databases such as Postgres, MySQL, or similar
  • ● Track record in architecting scalable data models and designing complex database schemas.
  • ● Comfort with ambiguity - you don't need a detailed spec to get moving.
  • ● It would be great if you also had . . .
  • ● Used or built MCP clients & servers, and understand how they operate under the hood
  • ● Implemented RBAC, authentication, or authorization flows in production systems
  • ● What will you be doing in this role
  • ● Architect and build fast, clean, and highly available backend systems in Python/FastAPI
  • ● Make the big architecture call. You'll own design decisions, not just implement someone else's diagram
  • ● Build and maintain our MCP gateway, the piece of infrastructure that lets AI tools talk to Clarivate's products
  • ● Deploy, run, and troubleshoot services on AWS
  • ● Use AI tools as part of your workflow (copilot, agents, LLM-based tooling). We want someone who thinks with AI, not just about it
  • ● Review code, swap feedback, and help each other write better software
  • ● Take a vague problem, run with it, and come back with a solution
  • ● Write tests that catch things, and docs that get read
  • ● About the Team
  • ● The team is a mix of backend engineers, frontend engineers, and data scientists. We keep processes lean - we focus on what works and iterate when it doesn't, rather than rigidly adhering to a specific methodology.
  • ● Hour of Work