This role involves building and scaling production-grade data infrastructure for agentic AI systems that perform complex tasks autonomously. The focus is on engineering resilient platforms for long-running workflows and multi-agent coordination in enterprise environments. The position emphasizes the importance of reliability, control, observability, and data governance. The successful candidate will work closely with data pipelines and integrations that connect agents to various enterprise data sources and tools.

• Master’s degree in software engineering, Computer Engineering, Information Technology, or related field with 5+ years of experience, or a PhD in the same fields with 3+ years of experience.
• Experience in DevOps, SRE, data engineering, or infrastructure engineering for production AI or distributed systems.
• Proficiency in Python for orchestration, data pipeline development, and platform automation.
• Experience with graph-based or agent orchestration frameworks.
• Experience building RAG and knowledge-graph-backed systems for LLM applications in production.

• Productionize graph-based orchestration for various patterns including planner-executor-validator and orchestrator-worker.
• Implement explicit state and control flows such as branching, loops, and human approval checkpoints.
• Enable robust agent-tool integration across APIs, services, and enterprise platforms.
• Design and maintain data pipelines connecting distributed enterprise data to a centralized knowledge layer.
• Build and operate event streaming and systems integration infrastructure for consistent data in agentic workflows.
• Define and track SLIs/SLOs for task completion reliability and tool-call success across agent pipelines.
• Implement CI/CD practices tailored for agent deployments, including versioning configurations and orchestration logic.
• Build incident response practices for autonomous workflows, including safe rollback and controlled retries.
• Implement full-stack observability for agent runs, including traces and data quality signals.
• Build continuous evaluation pipelines for agent behavior, focusing on correctness and safety.

• Intel offers a comprehensive benefits package including competitive pay, stock programs, healthcare coverage, retirement plans, paid time off, parental leave, and programs supporting employee wellbeing and professional development.