Senior AI Native Software Engineer (Agentic AI)

Dice is the leading career destination for tech experts at every stage of their careers. Our client, TekLeaders, Inc, is seeking the following. Apply via Dice today! Title: Senior AI Native Software Engineer (Agentic AI) Duration: 1 Year+ Contract Location: Remote with up to 20% travel required (travel will be reimbursed) Number of Openings: 15-20 Rate: only candidates who are eligible for W-2. Full Job Details We are looking for multiple AI Native Software Engineers to support our client's growing AI practice! What You 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)

What We'd Like You To Have

• 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

Responsibilities Will Include

• 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
• 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