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Tier-1 employer and popular GenAI role attract many applicants, despite niche agentic specialization.
Requires deep GenAI/LLM, agent orchestration and MLOps expertise, limiting cross-industry transferability.
Multiple mandatory technical filters: 7+ years, Python, GenAI/LLM experience, agent orchestration, and vector DBs.
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Architect and build enterprise-scale GenAI platforms focusing on reliability, scalability, and security.
Lead development of agentic AI systems including agent orchestration, multi-agent workflows, and tool execution layers.
Drive adoption of AI-assisted development tools and define standards, reusable components, and reference architectures for GenAI solutions with end-to-end ownership.
7+ years of engineering experience or equivalent (work experience, training, military experience, education).
Strong programming expertise in Python (mandatory).
Proven experience building GenAI / LLM-based applications and agent orchestration frameworks.
Experience with distributed systems architecture and context engineering, prompt design, memory management, LLM APIs, vector databases, and AI development tools like GitHub Copilot, Claude Code, or similar.
Experienced in designing multi-agent systems and autonomous frameworks within enterprise AI platforms.
Capable of leading high-impact AI projects delivering measurable business results in large, global organizations.
Familiar with secure and compliant AI systems governance, MLOps/LLMOps practices, preferably with financial services domain exposure.