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Tier-1 brand and metro location increase competition, despite senior, specialized ML requirements.
Deep LLM architecture, RAG, and agent expertise create high domain specificity.
Explicit 12–15 years plus mandatory LLM, cloud, containerization, and leadership requirements enforce high strictness.
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Lead design, development, and deployment of full stack AI platforms and microservices including RAG and multimodal LLM features.
Own end-to-end technical decisions balancing reliability, performance, and cloud cost across AI systems at enterprise scale.
Mentor engineers and partners, enforce code quality, run integrations, and drive Agile practices with focus on AI model testing and observability.
12-15 years professional experience with at least one general purpose programming language (Python preferred), and JavaScript/TypeScript frontend experience.
Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
Proven experience shipping scalable AI products incorporating LLMs, RAG, MCPs, and AI services in production.
Strong experience with cloud platforms (AWS, GCP, Azure), Docker, Kubernetes, and technical leadership including code reviews and quality assurance.
Senior engineer with demonstrated leadership in technical teams and managing external contractors or vendors.
Deep expertise in AI/ML architecture and system optimization, particularly in large-scale AI-powered features for 100k+ users.
Hands-on experience with multiple LLM providers, modern front-end frameworks, vector databases, and AI orchestration frameworks like LangChain or LlamaIndex.