AI Software Development Engineer

Intel Intel · Semiconductors · Arizona, Phoenix, United States +2

AI Software Development Engineer focused on building and scaling production-grade data infrastructure for agentic AI systems. Responsibilities include agent orchestration, data engineering and integration, DevOps for AI agent systems, and observability/evaluation for agent runs. Requires experience in DevOps, SRE, data engineering, or infrastructure engineering for production AI or distributed systems, LLM serving, RAG, and Python.

What you'd actually do

  1. Productionize graph-based orchestration for planner-executor-validator, orchestrator-worker, and similar patterns.
  2. Design and maintain data pipelines connecting distributed enterprise data to a centralized semantic/knowledge layer that ensures clean, unified inputs for agent consumption.
  3. Define and track SLIs/SLOs for task completion reliability, reasoning quality, tool-call success, latency, and cost across agent pipelines.
  4. Implement full-stack observability for agent runs - traces, state transitions, tool telemetry, data quality signals, outcomes, and replay ability.
  5. Build continuous evaluation pipelines for agent behavior, including correctness, safety, drift, and regression detection.

Skills

Required

  • DevOps
  • SRE
  • data engineering
  • infrastructure engineering for production AI or distributed systems
  • LLM serving
  • retrieval infrastructure
  • runtime control for non-deterministic systems
  • Graph-based or agent orchestration frameworks
  • RAG
  • knowledge-graph-backed systems for LLM applications in production
  • Python

Nice to have

  • multi-agent systems
  • production evaluation frameworks
  • observability and reliability for data and agent pipelines
  • Kubernetes
  • infrastructure as code
  • CI/CD
  • production observability
  • enterprise integration patterns and tools
  • developer-friendly tooling and documentation
  • regulated or enterprise environments

What the JD emphasized

  • production-grade data infrastructure for agentic AI systems
  • agentic AI systems
  • agent workflows
  • agentic platform
  • agentic AI systems
  • agent runs
  • agent behavior
  • agent quality and safety
  • agent pipelines

Other signals

  • productionize agent orchestration
  • build data pipelines for agents
  • define SLIs/SLOs for agent systems
  • implement observability for agent runs
  • build evaluation pipelines for agent behavior