AI Native Software Engineer

DATAEXL INFORMATION LLC is seeking an AI Native Software Engineer for a long-term contract role that involves designing and implementing AI agents and integrating AI systems into enterprise platforms. The candidate should have extensive experience in software engineering and leadership within enterprise-level environments.

Responsibilities:

• 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

Requirements:

• 8–10+ 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
• Experience with Infrastructure as Code
• Experience with Monitoring and observability tools
• Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)
• Candidates from enterprise-level environments
• Evaluate where they worked and what that organization actually does
• Must-have experience: Production-based AI applications
• Enterprise-scale delivery
• Not a fit: Candidates focused solely on proof-of-concept (POC) work
• Preferred seniority: Technical leaders, senior engineers, and architects who are able to be in the weeks in active development
• 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