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Senior, niche AI-cloud skillset in Bangalore reduces applicant density despite a generalist 'Engineering Lead' title.
Specialized LLM, vector DB, and regulated-pharma requirements moderately limit cross-industry portability.
Explicit 10+ years, 5+ years lead requirement and mandatory AI-cloud tech stack create stringent shortlisting filters.
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Lead technical architecture and AI strategy for custom enterprise solutions using Python, React, and cloud-native AI.
Drive end-to-end AI-augmented software development lifecycle, enforcing engineering quality, governance, and scalability standards.
Mentor engineers on AI tools, optimize cloud AI resource costs, and collaborate with business partners to implement Retrieval-Augmented Generation patterns.
10+ years in software engineering with 5+ years in a Technical Lead role.
Proficient in Python frameworks (FastAPI, Flask, Django) and React (TypeScript).
Hands-on experience with LLM integration, prompt engineering, and orchestration frameworks (e.g., LangChain, AutoGen, LlamaIndex).
Expertise in cloud platforms (Azure or AWS) with Infrastructure as Code (Terraform/Bicep) and experience building AI-ready CI/CD pipelines.
Experienced in AI-first software architecture and integrating Agentic AI/LLM workflows at enterprise scale.
Strong background in data architectures including SQL/NoSQL and vector databases for semantic search.
Skilled in AI governance, DevSecOps for AI, and cost-optimized cloud AI FinOps, particularly in regulated environments such as pharmaceuticals or finance.