Application Programming Interface (API), Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Debugging Skills, Distributed Computing, Diversity, Docker, Engineering, Java, Microservices, Open Source, People Management, Performance Modeling, Performance Testing, Performance Tuning/Optimization, Production Systems, Python Programming/Scripting Language, Scalable System Development, Software Engineering, System Integration (SI), Technical/Engineering Design, Test Strategy
AI Native Software Engineer
Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuses on implementing agent-based workflows, integrating AI platforms, 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
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)
TekWissen® Group is an equal opportunity employer supporting workforce diversity.