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Metro location plus broad AI/LLM requirements increases competition to medium density.
Role requires specialized LLM, RAG, and fine-tuning expertise, making cross-industry transferability limited.
Explicit 9-12 years plus many mandatory LLM, vector DB, and deployment skills makes filters very strict.
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Drive end-to-end delivery of complex AI projects including technical design, development, and implementation of scalable AI/ML models and applications.
Lead and mentor engineering teams on AI solutions, conduct architecture and code reviews ensuring quality, performance, and adherence to standards.
Design and implement advanced AI systems including LLM-based applications, RAG systems with vector and graph databases, multi-agent AI workflows, and secure integrations with enterprise ITSM tools.
9 to 12 years of professional experience in AI/ML engineering.
Bachelor's or Master's degree in Computer Science, AI/ML, or equivalent practical experience.
5+ years of Python development experience with strong software engineering fundamentals.
Hands-on experience with LLM APIs, TensorFlow, PyTorch, Hugging Face, vector and graph databases (Neo4j), cloud platforms (AWS), containerization (Docker, Kubernetes), and specifically AWS EKS and Istio/Kubernetes Gateway API.
Senior-level AI engineer comfortable leading complex projects and technical teams in delivering enterprise-scale AI solutions.
Expertise in designing multi-modal AI applications leveraging LLMs, vector search, knowledge graphs, and advanced model fine-tuning techniques (LoRA, QLoRA).
Experience managing secure, event-driven integrations and maintaining AI compliance with data anonymization and bias mitigation in cloud environments.