Senior Agentic AI Architect

Summary

We are seeking a visionary and hands-on Senior AI Agentic Architect to lead the strategic design, development, and deployment of next-generation autonomous AI agents and enterprise AI solutions. In this role, you will bridge the gap between cutting-edge artificial intelligence concepts and robust enterprise software engineering. You will be responsible for architecting scalable, cloud-native AI systems, driving the development of complex Retrieval-Augmented Generation (RAG) pipelines, and integrating intelligent agent workflows into our core business processes.
The ideal candidate possesses a deep understanding of cloud infrastructure, a vast knowledge of modern AI/ML paradigms (particularly LLMs and agentic frameworks), and a proven track record of bringing AI-powered software products from research to production.

Key Responsibilities

• Architect AI Agentic Systems: Lead the end-to-end architectural design of autonomous, multi-agent workflows and utility agents tailored to solve complex enterprise challenges and automate workflows.


• Cloud Infrastructure Design: Design, provision, and optimize scalable cloud infrastructure to support high-availability AI applications, ensuring secure and efficient deployment of models and agent logic.


• Product & Software Development: Actively participate in hands-on development, writing production-grade code to build and integrate AI/ML products within existing enterprise tech stacks and IT infrastructure.


• RAG & Search Optimization: Design and implement advanced custom RAG architectures and enterprise search solutions, actively identifying and mitigating challenges related to data ingestion, vector search


• optimization, and model hallucination.
  Technical Leadership & Strategy: Define and champion AI-centric software development methodologies. Evaluate new AI frameworks, tools, and platforms to ensure the organization remains at the forefront of AI innovation.


• Cross-functional Collaboration: Partner closely with data scientists, software engineers, DevOps, and business stakeholders to seamlessly deploy AI agents into production environments while adhering to enterprise security and networking standards (e.g., firewall integration, internal network components).

Critical Qualifications

• Programming Proficiency: Expert-level proficiency in Python, alongside experience with other modern programming languages (e.g., C#, Java). Building enterprise grade software solutions


• AI/ML Knowledge: Deep conceptual and practical understanding of generative AI, Large Language Models (LLMs), natural language processing (NLP), vector databases, and agentic orchestration frameworks.


• Cloud Infrastructure Expertise: Proven expertise in architecting and deploying applications on major cloud platforms (GCP preferred). Strong understanding of cloud-native architectures, containerization (Docker, Kubernetes), and CI/CD pipelines.


• Hands-On Development Experience: 7+ years of overall software engineering experience, with a significant portion dedicated to building and deploying AI/ML products or complex software applications.


• Systems Design Mindset: Exceptional ability to design complex distributed systems, with a strong grasp of API design, microservices architecture, and enterprise security principles.


• Education: Bachelor’s/Master’s in computer science, engineering, or a related field (or equivalent experience).

Preferred Qualifications

• Hands-on experience with Google Cloud Platform (GCP) and Vertex AI components (e.g., Vertex Search, Agent Development Kit, custom model deployment).


• Experience navigating complex enterprise internal networks and IT processes (e.g., managing network connectivity, security protocols).


• Familiarity with scrum, agile development frameworks.


• Strong understanding of emerging AI-centric development methodologies and frameworks (e.g. SDD, BMAD etc.)

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