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Mid-level experience and Bangalore metro increase competition, but niche agentic LLM tooling reduces applicant pool.
Highly domain-specific LLM, agentic workflows, and Claude/Cursor expertise reduce cross-industry transferability.
Mandatory 4–7 years plus specific Go/Python, Claude Code/Cursor, cloud, and Kubernetes make filters very strict.
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Drive adoption of AI-first engineering workflows organization-wide, implementing agentic AI practices across development lifecycle.
Build and maintain AI-powered internal agents, automation systems, and scalable backend services for smart TV and home entertainment products.
Design AI-enabled product features focused on search, recommendations, personalization, and automation while setting AI-native development standards.
4–7 years of backend engineering experience in production environments.
Strong hands-on experience with Go and Python.
Experience with Docker, Kubernetes, CI/CD, AWS, GCP, and backend systems including APIs, distributed systems, databases, caching, and observability.
Deep hands-on experience with Claude Code and Cursor; strong understanding of LLMs, model APIs, function calling, RAG, evals, and AI workflow orchestration.
Experienced backend engineer with proven ability to integrate AI tools into software development workflows at scale.
Comfortable owning end-to-end AI engineering pipelines from coding, testing, to deployment in a fast-paced startup setting.
Capable of influencing and mentoring engineering teams on AI-assisted development best practices while aligning AI capabilities with product outcomes.