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SYNCREON

AI Native Software Engineer – 50 to 70% Travel

SYNCREON

AI Native Software Engineer implementing AI-based systems, designing AI agents, and developing cloud-native services. Enhancing production quality and performance for enterprise-level applications in a remote capacity.

Posted 4/16/2026contractRemote • North Carolina • 🇺🇸 United StatesSeniorLead💰 $50,000 - $70,000 per yearWebsite

Tech Stack

Tools & technologies
CloudDockerJavaKubernetesMicroservicesPythonTerraform

About the role

Key responsibilities & impact
  • 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
  • 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
  • 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

Requirements

What you’ll need
  • 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
  • Infrastructure as code
  • Monitoring and observability tools
  • Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)

Benefits

Comp & perks
  • Remote work options
  • Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
PythonJavaAI agentsRetrieval (RAG)Microservices architectureContainersServerlessCI/CD pipelinesInfrastructure as codeMonitoring and observability