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Niche senior GenAI skillset and 10+ years experience limits competition despite remote option.
Highly specialized LLM/agentic AI and production ML expertise reduces cross-industry transferability.
Explicit 10+ years plus mandatory AI/LLM production and tooling requirements create strict shortlisting filters.
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Own architecture and technical direction for production-grade Agentic AI and Generative AI systems including LLM-powered multi-agent workflows and RAG pipelines.
Lead and mentor AI/ML and backend engineers while establishing engineering standards for scalable, reliable, and cost-efficient AI applications.
Collaborate cross-functionally with Product, Data, Platform, Security, and Compliance to deliver business-aligned, privacy and security-compliant AI solutions and represent AI engineering in strategic discussions.
10+ years of overall software engineering experience including 4+ years in AI/ML systems.
Minimum 2+ years hands-on experience building and deploying LLM-based or agentic AI applications in production.
Strong Python skills and experience building scalable distributed systems with microservices and cloud-native architecture on AWS, Azure, or GCP.
Experience with MLOps/LLMOps tools (e.g., MLflow, LangSmith, Weights & Biases) and knowledge of LLM fine-tuning techniques such as LoRA/PEFT and RLHF.
Experienced in designing complex AI architectures involving multi-agent systems, tool/function calling, memory management, and planning workflows.
Capable technical leader who provides architectural direction, mentors engineers, and drives best practices in production AI development.
Skilled communicator able to translate complex AI technical concepts for senior leadership and engage in strategic product and technology roadmap discussions.