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# Digital Design Flow Architect

- **Company:** NXP
- **Location:** Sunset Valley, TX, United States
- **Contract:** Permanent contract
- **Skills:** Computer-Aided Design, Artificial Intelligence, Systems Engineering, Audit Trail, Bash Shell, Databases, Computer Engineering, Software Debugging, Logic Synthesis of Circuits, Electronic Design Automation, Perl (Programming Language), JSON, Job Scheduling, Python (Programming Language), Release Management, Static Timing Analysis, Tcl (Programming Language), Retrieval-Augmented Generation, Multi-Agent Systems, Information Technology, Physical Design, Human in the Loop
- **Published:** October 30, 2026
- **Apply:** https://www.careerbuilder.com/job-details/digital-design-flow-architect-austin-tx--88d4902c-a7fc-48b7-b03e-ab8929af10bc

## About the Role

Graphic Design, Architectural Design, Artificial Intelligence (AI), Graphic Design, Architectural Design, Process Flow, Place and Route, Timing Verification, Debugging Skills, Analysis Skills, * Education: B.S. in Electrical Engineering, Computer Engineering, Computer Science, or related field required; M.S. or Ph.D. preferred.

 * Level: Director of Technology-level technical leader of digital design, CAD/methodology, EDA implementation, or flow architecture experience.
 * Scope: Proven ability to set technical direction, influence senior stakeholders, and lead cross-functional flow transformation across functional domains or technology nodes.

Required Experience and Skills

 * Deep hands-on experience in end-to-end digital implementation, RTL-to-GDS, static design and timing analysis, formal/static verification, signoff, ECO, and PPA closure.
 * Strong expertise in synthesis, floorplanning, place and route, clock-tree synthesis, power optimization, congestion analysis, and advanced-node implementation challenges.
 * Hands-on agentic AI workflow development experience, including task planning, tool invocation, result interpretation, retry logic, human-in-the-loop checkpoints, and autonomous execution patterns.
 * Practical MCP experience, including MCP clients/servers, tool and resource exposure, secure access, JSON-RPC-style communication, and integration with engineering systems.
 * Strong scripting and automation skills using Tcl, Python, Perl, shell, or equivalent flow automation technologies.
 * Experience with major EDA ecosystems such as Synopsys, Cadence, Siemens EDA, or equivalent internal platforms.
 * Ability to translate design challenges into repeatable methodology improvements, reusable automation, and measurable productivity gains.
 * Experience defining and executing deployment and migration strategies from current script-driven digital design flows to goal-driven agentic flows, including phased rollout, MCP/tool-adapter integration, validation against golden flows, human-in-the-loop checkpoints, observability, governance, rollback planning, and production adoption across RTL-to-GDS workflows., * Experience with AI-enabled EDA, agent orchestration, retrieval-augmented generation, multi-agent workflows, and workflow state management.
 * Experience developing MCP-enabled connectors or tool adapters for EDA tools, job schedulers, dashboards, repositories, databases, or compute environments.
 * Experience building production-quality flows with observability, auditability, permission control, evaluation harnesses, regression validation, documentation, and release management.

## Description

* Architect a modular RTL-to-GDS flow supporting synthesis, place and route, timing/power closure, static verification, signoff, and GDS delivery.
 * Enable agentic execution, AI-assisted debugging, design-space exploration, and automated analysis loops for EDA workflows.
 * Establish repeatable and traceable flow practices, including standard recipes, configuration baselines, metrics, dashboards, audit trails, regression checks, and release management.
 * Deploy flows for new process technologies in partnership with design, CAD/methodology, foundry, and EDA vendor teams.
 * Improve productivity, turnaround time, quality-of-results, and PPA through automation, methodology tuning, and scalable reuse.