Note: The job is a remote job and is open to candidates in USA. ClifyX is recruiting an Applied AI Engineer to build and operate production-grade AI and LLM systems serving users at scale. The role involves developing agentic systems, backend and distributed services, cloud infrastructure, containerized deployments, LLM integrations and evaluations, while writing code, debugging production issues, and deploying solutions.
Skills
- 10+ years
- 3+ years building production backend or distributed systems (pre-AI experience required)
- Has shipped AI/LLM features serving real users at scale — not just prototypes or demos
- Has built AI agents, skills, tools, or MCP (Model Context Protocol) integrations
- Proficient for backend development
- Working knowledge of Go, TypeScript, or Rust
- Deep experience with AWS/GCP/Azure — cost optimization, compute decisions, not just deployment
- Hands-on with Docker and Kubernetes — can build, deploy, debug, and scale services themselves
- Understands token economics, context limits, rate limiting, structured outputs, API failure modes
- Understands how to evaluate LLM outputs and the inherent challenges (non-determinism, quality measurement, regression detection)
- Not just an architect — writes code, debugs production issues, deploys their own work
- Built multi-step agentic workflows with tool use and function calling
- Experience with agent orchestration frameworks (LangGraph, CrewAI, Claude Agent SDK, Google ADK, OpenAI ADK)
- Built guardrails, fallbacks, or graceful degradation for AI systems
- Streaming inference and async agent orchestration
- Cost/latency optimization: caching, batching, prompt compression
- ML observability tools: Langfuse, Arize, Braintrust, W&B
- Retrieval systems (vector search, hybrid search) — as a tool, not the focus
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