Dice is the leading career destination for tech experts at every stage of their careers. Our client, Apolis, is seeking the following. Apply via Dice today!
Position: AI Native Software Engineers
Length: Long-term contract
Location: Remote
Pay rate- $70-75/hr on W2 (Only W2)
Job Description:
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
- 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
- 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
- Define and execute test strategies for AI systems
- Measure system performance (latency, throughput, accuracy, cost)
- Debug and optimize production systems
Must Have
- 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)
Required
- 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
Note - May require occasional travel to (Miami, Chicago, and/or Atlanta).