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AI Native Software Engineer – 50 to 70% Travel
SYNCREONAI 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 & technologiesCloudDockerJavaKubernetesMicroservicesPythonTerraform
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
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonJavaAI agentsRetrieval (RAG)Microservices architectureContainersServerlessCI/CD pipelinesInfrastructure as codeMonitoring and observability