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Metro location and popular senior AI title increase candidate density despite niche MLOps requirements.
Highly domain-specific ML/AI production skills and agent/RAG expertise limit cross-industry transferability.
Explicit 8+ years, 3+ years AI production, and extensive mandatory tech stack makes filters strict.
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Design, deploy, and operate scalable, production-grade AI systems and services across the enterprise AI platform.
Develop advanced AI capabilities including multi-agent systems, RAG pipelines, model training, fine-tuning, and deployment with continuous monitoring and compliance.
Build cloud-native microservices and responsive AI-powered user interfaces; own services from development through production support.
Bachelor's or Master's degree in Computer Science, AI, Engineering, or related field.
8+ years of software engineering experience, including 3+ years in production AI/ML applications.
Strong expertise in distributed systems, cloud-native architecture, microservices, and AI/ML frameworks and tools.
Proficient in Python, TypeScript/JavaScript, REST/gRPC, and cloud platforms (GCP and Azure).
Experienced in delivering enterprise-grade AI solutions from proof-of-concept to production in complex environments.
Skilled in modern AI lifecycle management including training, fine-tuning (LoRA/QLoRA/PEFT), hyperparameter optimization, and responsible AI practices.
Comfortable with cloud-native DevOps, CI/CD, and building secure scalable AI microservices with distributed tracing and observability.