Design and deploy production-grade AI systems using agent-based workflows, RAG, and cloud-native architectures. Build evaluation frameworks, implement observability & monitoring, and integrate AI platforms. Develop multi-model abstraction layers and optimize cost/performance.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Title: Sr. AI Engineering Architect
Position: 12+ months Contract
Location: 100% Remote job
Job Description:
Build and deploy production-grade AI systems using agent-based workflows, RAG, and cloud-native architectures within enterprise environments.
Key Responsibilities:
- Design AI agents (RAG, orchestration, tool/function calling, policy routing)
- Build evaluation frameworks (accuracy, latency, reliability)
- Implement observability & monitoring for AI systems
- Integrate AI platforms (OpenAI, Anthropic, Vertex AI, open-source models)
- Develop multi-model abstraction layers & optimize cost/performance
- Build scalable cloud-native apps (microservices, Docker, Kubernetes, serverless)
- Implement CI/CD pipelines & IaC (Terraform, Helm)
- Develop backend APIs & integrate with enterprise systems
- Test, debug, and optimize AI systems (latency, throughput, cost)
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Required Skills:
- 8–10+ years in software engineering
- Strong cloud-native experience (APIs, microservices, containers, serverless)
- Hands-on AI/LLM systems (agents, RAG, orchestration)
- Programming: Python / Java
- CI/CD, Infrastructure as Code, monitoring & observability
- Experience with AI platforms (OpenAI, Claude, Vertex AI)
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Preferred:
- Agent frameworks (LangGraph, AutoGen, CrewAI)
- Multi-agent/distributed AI systems
- Enterprise system integration
- AI cost & performance optimization
Expectations:
- 100% hands-on (no management)
- Production-quality delivery
- Work within existing architecture
- Collaborate with engineering teams
- Participate in implementation-focused design discussions
Regards
Mohd Faisal
908-279-1281
faisal@clifyx.com
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