Agentic/ Native AI Engineer

Job Summary
Overview

Seeking a hands-on AI Native Engineer 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 latencyCloud-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 toleranceApplication 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 workflowsTesting & Performance

Define and execute test strategies for AI systems Measure system performance (latency, throughput, accuracy, cost)
Debug and optimize production systems.Required Skills & 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)

Pay: $75.00 - $85.00 per hour

Work Location: Hybrid remote in Dallas, TX 75234