Job Details:Job Description: Build and scale production-grade data infrastructure for agentic AI systems that execute complex, multi-step work with autonomy, state, memory, and tool use. You will engineer resilient platforms for long-running agent workflows, multi-agent coordination, and adaptive execution in enterprise environments - while delivering the data pipelines and integrations that connect agents to enterprise data, legacy systems, and simulation tools. This role emphasizes reliability, control, observability, data quality, and governance for agentic AI systems over conversational chatbot patterns.
Key Responsibilities
Agentic Orchestration
• Productionize graph-based orchestration for planner-executor-validator, orchestrator-worker, and similar patterns.
• Implement explicit state and control flows: branching, loops, routing, interruption points, and human approval checkpoints.
• Enable robust agent-tool integration across APIs, services, data systems, and enterprise platforms.
• Support multi-agent collaboration patterns with guardrails for coordination, delegation, and convergence.
Data Engineering and Integration
• Design and maintain data pipelines connecting distributed enterprise data to a centralized semantic/knowledge layer that ensures clean, unified inputs for agent consumption.
• Build and operate event streaming, API management, and systems integration infrastructure to enable trustable, consistent data for agentic workflows.
• Build and maintain a data catalog and onboarding guides for teams adopting the agentic platform.
DevOps and Reliability for AI Agent Systems
• Define and track SLIs/SLOs for task completion reliability, reasoning quality, tool-call success, latency, and cost across agent pipelines.
• Implement CI/CD practices tailored for agent deployments - versioning agent configurations, prompts, tools, and orchestration logic as code.
• Build incident response and reliability practices for autonomous workflows, including safe rollback, pause/resume, and controlled retries.
• Optimize compute, storage, and inference paths for sustained agent throughput and cost efficiency.
Observability, Evaluation, and Control
• Implement full-stack observability for agent runs - traces, state transitions, tool telemetry, data quality signals, outcomes, and replay ability.
• Build continuous evaluation pipelines for agent behavior, including correctness, safety, drift, and regression detection.
• Provide actionable operational dashboards for quality, reliability, data health, and cost in production agent systems.
Qualifications:Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Minimum Qualifications
- Master’s degree in software engineering, Computer Engineering, Information Technology, or related field with 5+ years of experience.
- OR PhD in Software Engineering, Computer Engineering, Information Technology, or related field with 3+ years of experience.
Experience listed above should be in at least one of the following:
- DevOps, SRE, data engineering, or infrastructure engineering for production AI or distributed systems.
- LLM serving, retrieval infrastructure, and runtime control for non-deterministic systems.
- Graph-based or agent orchestration frameworks.
- Experience building RAG and knowledge-graph-backed systems for LLM applications in production.
- Python skills for orchestration, data pipeline development, and platform automation
Preferred Qualifications
• Experience designing multi-agent systems with clear autonomy boundaries and human-in-the-loop controls.
• Track record in production evaluation frameworks for agent quality and safety.
• Experience with observability and reliability for data and agent pipelines (metrics, logging, tracing, data quality monitoring).
• Strong experience with Kubernetes, infrastructure as code, CI/CD, and production observability.
• Deep experience with enterprise integration patterns and tools (e.g., RBAC, ABAC).
• Ability to package data engineering practices into developer-friendly tooling and documentation.
• Experience in regulated or enterprise environments requiring high trust and auditability.
Job Type:Experienced Hire
Shift:Shift 1 (United States of America)
Primary Location: US, Arizona, Phoenix
Additional Locations:US, California, Folsom, US, Oregon, Hillsboro
Business group:Intel Foundry strives to make every facet of semiconductor manufacturing state-of-the-art while delighting our customers -- from delivering cutting-edge silicon process and packaging technology leadership for the AI era, enabling our customers to design leadership products, global manufacturing scale and supply chain, through the continuous yield improvements to advanced packaging all the way to final test and assembly. We ensure our foundry customers' products receive our utmost focus in terms of service, technology enablement and capacity commitments. Employees in the Foundry Technology Manufacturing are part of a worldwide factory network that designs, develops, manufactures, and assembly/test packages the compute devices to improve the lives of every person on Earth.
Benefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $195,200.00-275,580.00 USD
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.
Work Model for this Role
This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.
*
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.
