AI Architect

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

☁️ SaaS

🎯 Recruiter

Human Resources • SaaS • Recruitment

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• Lead the design, architecture, and deployment of enterprise-grade AI solutions built on modern agentic AI frameworks. • Define end-to-end AI architecture, establish governance standards, and ensure scalable, secure, and production-ready AI systems. • Collaborate with engineering teams, solution architects, business stakeholders, and client leadership to transform complex business challenges into innovative AI-driven solutions. • Establish AI architecture standards, define governance and observability frameworks, ensure regulatory compliance, and drive technical excellence across multiple engagements.

🎯 Requirements

• 7+ years of overall technology experience • 6–8 years of overall technology experience with 3–5 years of hands-on experience building and deploying production-grade AI or Agentic AI systems. • Proven expertise in designing and implementing multi-agent AI architectures for enterprise environments. • Strong experience with AWS cloud services, including Amazon Bedrock, SageMaker, Lambda, API Gateway, and AI-focused cloud architectures. • Deep understanding of Agentic AI concepts, including orchestration, RAG, memory architectures, AI evaluation, and guardrail implementation. • Experience integrating AI solutions with enterprise applications, hybrid infrastructure, identity management systems, and secure networking environments. • Strong knowledge of AI governance, explainability, observability, compliance, risk management, and responsible AI practices. • Expertise in defining AI monitoring frameworks, model evaluation strategies, drift detection, and production reliability standards. • Excellent understanding of enterprise architecture principles, cloud-native application design, and distributed systems. • Strong stakeholder management and communication skills with the ability to present technical strategies to both technical and executive audiences. • Experience supporting solution architecture, technical pre-sales, estimation, and delivery governance. • Demonstrated leadership skills with the ability to mentor engineering teams and drive architectural excellence across multiple projects. • Exposure to multi-cloud environments and enterprise-scale digital transformation initiatives is an added advantage.