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)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 91143520
- Position Id: 2026-43
- Posted 4 hours ago
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