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Junior, popular AI role in Bangalore with broad toolset requirements increases applicant density.
ML/AI production and LLM experience is transferable but needs specific tooling and cloud familiarity.
Mandatory hands-on LLM, cloud, and production deployment skills create moderate filtering.
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Own end-to-end development of AI-powered tools from functional requirements through production deployment and iteration, rather than just prototypes.
Design and implement cloud- and platform-agnostic AI solutions, working across multi-cloud environments and various AI tooling including LLM APIs, agents, and workflow automation.
Contribute broadly on a small, fast-moving team wearing multiple hats initially; progressively specialize and take ownership of architecture and identity services like Azure/Entra as team grows.
At least 1 year of experience demonstrating end-to-end ownership in Python development including backend and frontend-adjacent work.
Strong understanding of serverless and cloud services from first principles; platform-agnostic multi-cloud experience including Azure, AWS, or GCP.
Hands-on experience with LLM APIs, agents, tool/function calling, and AI-assisted development workflows such as Claude Code.
Proficient with Git/GitHub, basic CI/CD pipelines (GitHub Actions or equivalent), and writing well-tested, reliable production code.
Technically strong individual contributor comfortable reasoning from fundamentals to architect scalable AI solutions across cloud platforms without reliance on vendor-specific knowledge.
Experienced in integrating multiple AI/LLM models, automations, and workflows to deliver client-facing or internal business value with production resilience.
Growth-oriented developer who thrives in a small team environment, able to self-direct scope in ambiguous contexts and progressively assume architecture ownership and identity management specialization (Azure/Entra).