Agentic AI Software Engineer
Job in
Jacksonville, Duval County, Florida, 32211, USA
Listed on 2026-06-02
Listing for:
Saxon Global
Full Time
position Listed on 2026-06-02
Job specializations:
-
Software Development
AI Engineer, Cloud Engineer - Software, DevOps, Machine Learning/ ML Engineer
Job Description & How to Apply Below
- 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)
- Experience with agent frameworks (e.g., Lang Graph, Auto Gen, CrewAI)
- Experience designing multi-agent or distributed AI systems
- Familiarity with enterprise-scale system integration
- Experience optimizing AI workloads for cost and performance
- 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
- Develop scalable services using:
- 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
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