Agentic AI Architect

Tiger Analytics Inc.

2d

About The Position

Tiger Analytics is seeking an experienced Agentic AI Architect with generative AI experience to design and bootstrap next-generation Agentic AI architecture. The role bridges business strategy and technical execution, designing scalable multi-agent AI ecosystems on Azure, AWS, or GCP while remaining hands-on with prototypes, design patterns, and code reviews. The architect will work with business executives and engineering teams to turn AI product visions into production-ready enterprise platforms.

The role is divided among architecture and solution design (50%), hands-on engineering and prototyping (30%), and stakeholder collaboration and leadership (20%). Responsibilities include designing secure and scalable agent architectures and cognitive workflows; establishing cloud-native pipelines, orchestration, memory, and state-management patterns; integrating agents with enterprise systems; building prototypes and MVPs; evaluating frameworks and models; translating business problems into technical requirements; advising and educating stakeholders; and collaborating on AI governance and safety.

Tiger Analytics is an advanced analytics consulting firm whose employees work in machine learning, data science, and AI, and which serves multiple Fortune 500 companies. The position offers significant career development opportunities in a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility. Applicants based in the US and Canada are invited to apply. Tiger Analytics provides equal employment opportunities without regard to protected characteristics or status under applicable law.

Requirements

• At least 5 years of experience architecting cloud solutions on at least one major hyperscaler: Azure, AWS, or GCP.
• At least 2 years of direct experience working with LLMs and building complex AI applications, such as RAG pipelines, autonomous agents, or tool-calling systems.
• Hands-on proficiency with agent orchestration frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI, or LangChain.
• Strong production-grade programming skills in Python (preferred), TypeScript, or Java.
• Experience with CI/CD pipelines for AI (LLMOps).
• Proven experience with vector databases and enterprise search engines.
• Ability to explain complex machine learning or architectural concepts clearly to non-technical business leaders.
• A pragmatic approach balancing emerging AI trends with stable, cost-effective enterprise software.
• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field, or equivalent practical experience.

Nice To Haves

• Azure Solutions Architect Expert or Azure AI Engineer Associate certification.
• AWS Certified Solutions Architect – Professional or AWS Certified Machine Learning – Specialty certification.
• Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer certification.

Responsibilities

• Design robust, secure, and scalable architectures for autonomous and semi-autonomous AI agents, multi-agent orchestration systems, and cognitive workflows.
• Architect cloud-native AI pipelines using services on Azure, AWS, or GCP.
• Establish patterns for LLM orchestration, semantic memory storage, and state management.
• Integrate AI agents with legacy enterprise systems, APIs, RPA tools, and real-time data streams, optimizing cost, latency, and throughput.
• Build proof-of-concepts and minimum viable products to validate architectural approaches and de-risk complex agent workflows.
• Establish production-grade AI engineering coding standards and conduct code reviews for reliability, security, and prompt/agent behavior.
• Evaluate emerging AI frameworks, tools, and foundational models for enterprise viability.
• Translate business problems into structured agentic workflows and concrete technical requirements in partnership with product managers and business stakeholders.
• Educate engineering teams and advise executives on Agentic AI capabilities, limitations, and ROI.
• Collaborate with Security, Compliance, and Risk teams to design AI guardrails and support privacy, hallucination mitigation, and ethical AI deployment.

Benefits

• Significant career development opportunities.
• Opportunity to work in a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior