Agentic AI Lead / Architect

San Diego, CA / Austin, TX / Fort Mill, SC • Full Time

About the role

Lead the architecture, design, and implementation of enterprise‑grade Agentic AI platforms and applications using Generative AI, LLMs, RAG, and multi‑agent architectures.

Responsibilities

• Design, develop, and deploy autonomous AI agents using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, and LangChain.
• Build scalable, secure, highly available AI solutions on AWS, leveraging services including Bedrock, Lambda, ECS/EKS, SageMaker, API Gateway, DynamoDB, S3, and CloudWatch.
• Define enterprise architecture patterns, technical standards, governance, security, monitoring, observability, scalability, and performance best practices for AI solutions.
• Collaborate with business stakeholders, clients, product teams, and engineering teams to translate complex business requirements into AI‑driven solutions.
• Lead technical teams through solution design, development, deployment, optimization, and architecture governance while mentoring engineers and driving technical decisions.
• Conduct client workshops, architecture reviews, technical presentations, and executive discussions.

Requirements

• 10+ years of software engineering experience, including 3+ years of experience in AI/ML, Generative AI, or AI solution architecture.
• Proven experience designing and delivering at least one production‑grade Agentic AI platform within an enterprise environment.
• Preferred experience in Financial Services, Capital Markets, Banking, Trading, or Investment Management.

Skills

• Strong hands‑on expertise in Python for developing scalable AI applications, services, and automation workflows.
• Experience with AI agent frameworks: LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain.
• Proficiency with AWS services: Bedrock, Lambda, ECS/EKS, SageMaker, API Gateway, DynamoDB, S3, CloudWatch.
• Design and implementation of RAG architectures, vector databases, prompt engineering, AI evaluation, and AI observability solutions.
• Solid knowledge of software architecture, distributed systems, microservices, API design, and cloud‑native application development.