TekWissen ®Remote
AI Native Software Engineer
United States of America
Contract
6 days ago
$70 - $90 USD
H1B Sponsor Likely
Key skills
PythonJavaAILLMOpenAIClaudeAnthropicRAGAutoGenLangGraphTerraformKubernetesDockerServerlessHelmVertex AICI/CD
About this role
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. They are seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments, focusing on implementing agent-based workflows and delivering scalable cloud-native solutions.
Responsibilities:
- AI Agent Engineering
- 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
- 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
Requirements:
- 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., 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