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Tier-1 brand, generalist AI title, and metro location create high candidate competition density.
Core LLM and cloud skills are transferable, but edge, audio, and industrial telemetry requirements increase domain specificity to medium.
Role demands specialized LLM, RAG, edge deployment, speech-to-text, and cloud skills, enforcing strict candidate filters.
Develop and maintain AI software features including Generative AI, LLM applications, Retrieval-Augmented Generation (RAG), vector databases, and semantic search systems.
Design and deploy AI workflows, speech-to-text, voice assistants, signal processing for sensor data, and real-time AI model inference on edge devices and cloud (AWS).
Collaborate in Agile teams on backend AI services, APIs, model evaluation, prompt engineering, and architecture/code quality reviews.
Work Experience Required: Not explicitly mentioned in the JD
Experience with AI software development including Generative AI, LLMs, RAG, vector DB pipelines, and semantic search.
Proficiency in deploying AI solutions on cloud platforms (AWS) and edge/embedded systems with real-time inference needs.
Familiarity with Agile software development processes and building backend services and APIs for enterprise AI platforms.
Candidate skilled in end-to-end AI software engineering from model development to deployment in scalable cloud and edge environments.
Experienced in integrating advanced AI workflows including autonomous multi-agent systems, speech and audio analytics.
Able to contribute to team architecture and code quality initiatives within Agile frameworks, indicating mid to senior level software engineering capability in AI domain.