AI Architect--100% remote Job-15 + years exp

Overview
Seeking a hands-on AI Native Software Architect to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuses on implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions. Responsibilities
AI Agent Engineering
Design and implement AI agents, including:
Retrieval (RAG)
Orchestration workflows
Tool/function invocation
Policy-based routing
Build evaluation frameworks for accuracy, latency, and reliability
Implement observability and monitoring for agent lifecycle.

AI Platform Integration
Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models)
Build abstraction layers to support multi-model and multi-provider architectures
Optimize model usage for performance, cost, and latency
Cloud-Native Development
Develop scalable services using:
Microservices architecture
Containers (Docker, Kubernetes)
Serverless and event-driven patterns
Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm)
Ensure production readiness, logging, monitoring, and fault tolerance
Application Development
Build and deploy AI-powered applications aligned to business workflows
Integrate AI systems into existing enterprise platforms and APIs
Develop backend services and APIs supporting agent workflows
Testing & Performance
Define and execute test strategies for AI systems
Measure system performance (latency, throughput, accuracy, cost)
Debug and optimize production systems.

Required Skills & Experience
12+ years of software engineering experience
Strong experience with cloud-native systems (APIs, microservices, containers, serverless)
Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration)
Proficiency in Python, Java, or similar backend languages
Experience with:
CI/CD pipelines
Infrastructure as code
Monitoring and observability tools
Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)
Preferred Experience
Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI)
Experience designing multi-agent or distributed AI systems
Familiarity with enterprise-scale system integration
Experience optimizing AI workloads for cost and performance.

Scope & Expectations
100% hands-on engineering role (no people management)
Deliver production-quality code and deployments
Work within existing architecture and engineering standards
Collaborate with client and internal engineering teams as needed
Participate in technical design discussions (implementation-focused)