Agentic AI Architect

Job Description

This role is for one of the Weekday's clients

Salary range: Rs 2000000 - Rs 5000000 (ie INR 20-50 LPA)

Experience: 7+ yrs

Location: Remote (India), India

Job Type: full-time

We are seeking an experienced Agentic AI Architect to lead the design, architecture, and deployment of enterprise-grade AI solutions built on modern agentic AI frameworks. This is a senior, hands-on technical leadership role responsible for defining end-to-end AI architecture, establishing governance standards, and ensuring scalable, secure, and production-ready AI systems. The ideal candidate will have extensive experience designing and deploying multi-agent AI applications, integrating AI with enterprise ecosystems, and leveraging AWS cloud services to deliver intelligent business solutions.

In this role, you will collaborate with engineering teams, solution architects, business stakeholders, and client leadership to transform complex business challenges into innovative AI-driven solutions. You will be responsible for establishing AI architecture standards, defining governance and observability frameworks, ensuring regulatory compliance, and driving technical excellence across multiple engagements.

Requirements

Key Responsibilities

• Design and architect enterprise-scale multi-agent AI systems with a focus on scalability, security, and reliability.
• Develop intelligent AI solutions utilizing agent orchestration, Retrieval-Augmented Generation (RAG), memory management, evaluation frameworks, and AI guardrails.
• Architect AI platforms using AWS services, including Amazon Bedrock, SageMaker, Lambda, API Gateway, and related cloud-native technologies.
• Design secure AI integrations with enterprise applications, legacy systems, identity management platforms, virtual private clouds, and hybrid cloud environments.
• Define AI governance frameworks covering explainability, monitoring, compliance, observability, auditability, and responsible AI practices.
• Establish production standards for AI model evaluation, drift detection, reliability testing, and continuous performance monitoring.
• Conduct architecture reviews to ensure engineering solutions align with enterprise security, scalability, and operational standards.
• Develop reusable architecture patterns, technical documentation, implementation frameworks, and best practices for AI solution delivery.
• Collaborate with cross-functional teams to translate business requirements into robust AI architecture and implementation roadmaps.
• Support pre-sales engagements through solution design, technical workshops, effort estimation, and client presentations.
• Provide technical leadership and mentorship to engineering teams, promoting high-quality AI engineering practices.
• Stay current with advancements in Agentic AI, Generative AI, cloud technologies, and enterprise AI governance to drive continuous innovation.

What Makes You a Great Fit

• 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.