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Tier-1 brand and metro location increase applicant density, but senior AI platform specialization narrows the pool.
Highly domain-specific LLM, AI-platform and model engineering requirements limit cross-industry transferability.
Requires proven AI platform engineering leadership, LLM expertise and AWS/platform experience, creating strict shortlisting filters.
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Lead engineering teams to build and operate LLM-based conversational AI platforms and foundational capabilities enabling multi-domain product contributions.
Design, develop, and maintain Model Context Protocol (MCP) servers, platform SDKs, and extensible architectures ensuring scalability, security, and ease of integration for conversational AI channels.
Drive adoption of AI-driven software engineering practices to improve engineering throughput, development workflows, and platform reliability across teams.
Proven experience leading engineering teams in AI-enabled or platform system contexts.
Hands-on experience designing, building, and operating platform components, APIs, or SDKs used by multiple product teams.
Knowledge of LLM technologies, evaluation, prompting, retrieval techniques, safety, and AWS-based system scaling.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced technical leader comfortable in hands-on architectural decisions and platform strategy focused on conversational AI and LLM systems.
Strong focus on building reusable, scalable, extensible platforms enabling other product teams to integrate conversational AI features with minimal friction.
Proven track record of influencing cross-team adoption measured by platform usage metrics, developer experience, and engineering throughput improvements.