Title: AI Native Software Engineer Duration: 12 Months
Job description:
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 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 Required Skills & Experience 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) Preferred Experience 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 Scope & Expectations 100% hands-on engineering role (no people management)Deliver production-quality code and deployments Work within existing architecture and engineering standards Collaborate with client and internal engineering teams as needed Participate in technical design discussions (implementation-focused)
Required Skills:
OpenAir
Title: AI Native Software EngineerDuration: 12 MonthsJob description:Responsibilities:AI Agent EngineeringDesign and implement AI agents including: Retrieval (RAG) Orchestration workflows Tool/function invocation Policy-based routingBuild evaluation frameworks for accuracy latency and reliability Im...
Title: AI Native Software Engineer Duration: 12 Months
Job description:
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 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 Required Skills & Experience 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) Preferred Experience 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 Scope & Expectations 100% hands-on engineering role (no people management)Deliver production-quality code and deployments Work within existing architecture and engineering standards Collaborate with client and internal engineering teams as needed Participate in technical design discussions (implementation-focused)