AI Application Architect

Role Name: AI Application Architect
Location: California City, CA ( Onsite ) Local Candidates Only
Visa : GC
Job Type: Full Time
Experience: 16+ Years
Interview Mode: Virtual
Pay Rate: Based on Experience

Job Description:

We are seeking a highly experienced AI Application Architect to architect, design, and guide the development of enterprise-grade AI agent applications and intelligent enterprise solutions. The ideal candidate will have 16+ years of software/application architecture experience with strong hands-on expertise in AI/LLM technologies, agentic frameworks, Python, AWS, distributed systems, and cloud-native architectures.

The AI Application Architect will be responsible for defining technical architecture, integration patterns, security standards, scalability strategies, and implementation approaches for production-ready AI agents and enterprise tool integrations.

Key Responsibilities:

• Define and lead the architecture and technical design of enterprise-grade AI agent applications.
• Collaborate with business, product, engineering, security, and cloud teams to define AI solution requirements, architecture, integration patterns, and implementation strategies.
• Design orchestration agents and domain-specific agents using Python 3.12, LangChain, LangGraph, or Strands.
• Architect solutions integrating LLMs and foundation models for reasoning, structured responses, tool calling, and workflow execution.
• Define architecture and deployment strategies for AI agents using Amazon Bedrock AgentCore Runtime.
• Architect agent-to-agent communication using A2A 1.0 and the official Python a2a-sdk.
• Design secure agent-to-tool integrations using Model Context Protocol (MCP) and Amazon Bedrock AgentCore Gateway.
• Define data architecture using PostgreSQL for task persistence, workflow status, agent state, and idempotency management.
• Architect secure document and artifact management using Amazon S3 and credential management through AWS Secrets Manager.
• Define observability architecture using AgentCore Observability, OpenTelemetry, and Amazon CloudWatch.
• Establish standards for logging, metrics, distributed tracing, monitoring, security, scalability, and reliability of AI applications.
• Define testing strategies covering unit, integration, A2A contract, performance, and end-to-end testing using tools such as pytest.
• Evaluate emerging AI technologies, agentic frameworks, protocols, and cloud services for enterprise adoption.
• Establish architecture standards, reusable patterns, technical guidelines, and best practices for AI application development.
• Provide technical leadership and mentorship to AI engineers and development teams.
• Review architecture, source code, integration designs, and implementation approaches to ensure alignment with enterprise standards.
• Troubleshoot complex architectural and production issues involving AI applications, distributed systems, APIs, cloud infrastructure, and integrations.

Qualifications:

• Experience: 16+ years of experience in software engineering, application architecture, solution architecture, or related technology roles, with significant experience designing enterprise applications.
• AI & LLM Architecture: Proven experience architecting AI applications and integrating LLMs/foundation models with enterprise systems.
• Python Engineering: Strong proficiency in Python 3.12+, asynchronous programming, API development, and object-oriented design.
• Agentic AI: Hands-on architecture experience with LangChain, LangGraph, Strands, or similar agentic AI frameworks.
• Prompt Engineering: Strong understanding of prompt engineering, tool calling, structured outputs, context management, and LLM response validation.
• Cloud & APIs: Strong experience with AWS services, REST APIs, relational databases, and cloud-native application architecture.
• Architecture: Strong understanding of multi-agent orchestration, distributed systems, event-driven architecture, task persistence, asynchronous workflows, scalability, and high availability.
• Enterprise Integration: Experience designing integrations between AI agents, enterprise applications, APIs, databases, and external tools.
• Security: Strong understanding of secure AI application architecture, authentication, authorization, secrets management, data protection, and enterprise security standards.
• Leadership: Strong technical leadership, architecture governance, problem-solving, communication, and cross-functional collaboration skills.
• Education: Bachelor s or Master s degree in Computer Science, Engineering, or a related field.

Preferred Skills:

• AWS Bedrock Stack: Experience architecting solutions using Amazon Bedrock, AgentCore Runtime, AgentCore Gateway, and AgentCore Observability.
• Protocols & MCP: Strong knowledge of A2A protocols, MCP clients and servers, and enterprise tool integration.
• Infrastructure & Tools: Experience with PostgreSQL, Amazon S3, AWS Secrets Manager, OpenTelemetry, CloudWatch, HashiCorp, and pytest.
• Production Architecture: Experience architecting secure, scalable, highly available, and production-grade AI applications.
• DevOps & MLOps: Experience with Docker, Kubernetes, CI/CD pipelines, RAG, LLM evaluation, AI guardrails, and cloud-native deployment.
• Experience designing multi-agent systems and agent orchestration architectures.
• Experience with AI governance, responsible AI, observability, model evaluation, and enterprise AI security.
• Experience working with large-scale distributed systems and high-volume enterprise applications.