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Ai Chip Design Rtl Jobs in Virginia (NOW HIRING)

Geologics

Digital Design Engineer

Manassas, VA · On-site

$67/hr

Understanding of System-On-Chip (SoC) design with embedded processor on FPGA * Ability to perform application programming on embedded processor is a plus * Identifies opportunities to apply AI for ...

Geologics

Digital Design Engineer

Manassas, VA

$67/hr

Understanding of System-On-Chip (SoC) design with embedded processor on FPGA * Ability to perform application programming on embedded processor is a plus * Identifies opportunities to apply AI for ...

Leidos

FPGA Firmware Design Engineer

Arlington, VA · On-site

... RTL and incorporate client feedback into firmware revisions. This role will also support ... Experience with latest System on a Chip (SoC) implementations such as AMD/Xilinx Ultrascale ...

CRDF Global

Emerging Technology Experts

Arlington, VA · On-site

... safety, AI applications in cyber defense and critical infrastructure. Astronautics & Space ... Microelectronics & Semiconductors Chip design (EDA tools), lithography, fabrication, packaging and ...

Leidos

FPGA Firmware Design Engineer

Arlington, VA · On-site

... RTL and incorporate client feedback into firmware revisions. This role will also support ... a Chip (SoC) implementations such as AMD/Xilinx Ultrascale+ /Versal series and Altera Agilex/MCP ...

Leidos

FPGA Firmware Design Engineer

Arlington, VA

$87K - $157K/yr

... RTL and incorporate client feedback into firmware revisions. This role will also support ... a Chip (SoC) implementations such as AMD/Xilinx Ultrascale+ /Versal series and Altera Agilex/MCP ...

CRDF Global

Emerging Technology Experts

Arlington, VA · On-site

Frontier models (large language models, foundation models), adversarial AI, AI red-teaming, ethics ... Chip design (EDA tools), lithography, fabrication, packaging and assembly/test, semiconductor ...

Neuroscale AI

Forward Deployed Engineer

Reston, VA · On-site

Our momentum is further fueled by blue-chip partners and programs, including the NVIDIA Inception ... You will write code, design integrations, build prototypes, configure AI workflows, troubleshoot ...

NewGen

Electrical Engineer

Arlington, VA · On-site

Lead technical design and setup of Chip-Off Forensics Lab infrastructure at government facility ... We have helped secure borders, have used artificial intelligence (AI) to fight terror, aided the ...

NewGen Technologies

Electrical Engineer

Arlington, VA · On-site

Lead technical design and setup of Chip-Off Forensics Lab infrastructure at government facility ... We have helped secure borders, have used artificial intelligence (AI) to fight terror, aided the ...

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All JobsAi Chip Design Rtl JobsAi Chip Design Rtl Jobs in Virginia

Ai Chip Design Rtl information

What is the difference between Ai Chip Design Rtl vs Ai Chip Verification Engineer?

AspectAi Chip Design RtlAi Chip Verification Engineer
Primary FocusDeveloping and implementing Register Transfer Level (RTL) code for AI chipsVerifying and validating RTL designs to ensure functionality
Skills RequiredHDL languages (Verilog/VHDL), digital design, FPGA/ASIC knowledgeSimulation, testbench creation, debugging, scripting skills
Work EnvironmentDesign teams, hardware development labs, EDA toolsVerification teams, simulation environments, test setups
CertificationsHardware design certifications, FPGA/ASIC trainingVerification methodologies, UVM, SystemVerilog certifications

While Ai Chip Design Rtl focuses on creating the hardware description code for AI chips, Ai Chip Verification Engineer ensures that the RTL design functions correctly through rigorous testing. Both roles require knowledge of HDL languages and work closely within hardware development teams, but their core responsibilities differ—design versus verification.

What are some common challenges faced by AI Chip Design RTL engineers during the verification process?

AI Chip Design RTL engineers often encounter challenges in ensuring their designs meet complex functional and performance requirements, especially given the rapid pace of AI hardware advancements. Verification can be particularly demanding due to the need to simulate and test intricate AI workloads, manage large datasets, and debug subtle timing or logic errors. Collaboration with verification teams, system architects, and software engineers is essential to address these issues efficiently and to ensure seamless integration of the RTL code into the broader chip design. Staying up-to-date with the latest verification tools and methodologies is also crucial for success in this role.

What are AI Chip Design RTL engineers?

AI Chip Design RTL (Register Transfer Level) engineers are specialists who design the digital logic for chips used in artificial intelligence applications. They use hardware description languages like Verilog or VHDL to create and validate the architecture and functionality of these chips before they are manufactured. Their work ensures that AI processors are efficient, high-performing, and meet the requirements of modern AI workloads. RTL engineers collaborate closely with verification, software, and hardware teams to optimize chip performance and power consumption.

What are the key skills and qualifications needed to thrive as an AI Chip Design RTL Engineer, and why are they important?

To thrive as an AI Chip Design RTL Engineer, you need a solid background in digital design, computer architecture, and proficiency in Hardware Description Languages (HDLs) like Verilog or VHDL, often supported by a degree in electrical or computer engineering. Experience with simulation tools (e.g., ModelSim, Synopsys), ASIC/FPGA design flows, and relevant certifications are highly valued. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills help you excel in collaborative and complex design environments. These competencies are crucial for creating efficient, reliable AI hardware that meets performance and power requirements in a fast-evolving field.
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Infographic showing various Ai Chip Design Rtl job openings in Virginia as of June 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.
AI Infrastructure Engineer - Emerging Technologies

AI Infrastructure Engineer - Emerging Technologies

Cologix

Ashburn, VA

$109K - $144K/yr

Full-time

Posted 6 days ago

Job description

About Our Company:
Headquartered in Denver, Colorado, Cologix is a leading North America network-neutral interconnection and hyperscale edge data center company. Our platform gives customers access to 45+ digital edge and Scalelogix hyperscale edge data centers in 13 markets across the United States and Canada along with a carrier-dense ecosystem of 710+ networks, 360+ cloud providers, 35+ onramps and seven Internet exchanges. We provide our nearly 2,000 customers with direct access to our local operations teams, resulting in strong partnerships enabled by exceptional operational support and unparalleled customer service. Backed by one of the largest North American infrastructure funds, Cologix's experienced leadership team, certified staff and commitment to ESG initiatives help form a culture that values our people, our environment and our clients.

About the Position:

The AI Infrastructure Engineer - Emerging Technologies will support the Office of the VP of Technology Engineering & Innovation in evaluating, designing, and developing next-generation AI-ready data center infrastructure strategies.

This role serves as a bridge between emerging AI technologies and practical implementation across data center development, engineering, construction, operations, and energy infrastructure planning.

The position will focus on assessing how rapidly evolving AI compute architectures, high-density rack deployments, advanced cooling systems, and emerging power technologies will impact future data center design standards, development strategies, construction methodologies, and operational models.

The ideal candidate combines expertise in AI infrastructure, power systems, cooling technologies, and emerging compute platforms with the ability to translate industry trends into actionable engineering and infrastructure strategies for future AI-enabled data center environments.

This role is ideal for someone who is highly analytical, technically curious, and capable of bridging emerging AI compute trends with real-world infrastructure strategy and execution. This individual should be comfortable operating across engineering, operations, construction, energy strategy, and innovation functions while helping shape the future direction of AI-enabled data center development.

This role will help evaluate and guide the following areas:

  • Future AI rack density and power consumption trends
  • Impacts of next-generation GPU and AI chip architectures
  • Optical networking and switching implications on infrastructure design
  • AI workload impacts on utility infrastructure and power quality
  • Evolution of liquid cooling and high-density thermal management
  • Grid-parallel and microgrid strategies for AI campuses
  • Future AI-ready development and construction standards
  • Long-term AI infrastructure innovation roadmaps
  • Vendor technology evaluation and infrastructure modernization strategies
What you do daily:

AI Infrastructure Strategy & Analysis

  • Support the VP of Technology Engineering & Innovation in evaluating emerging AI infrastructure technologies and future-ready data center strategies.
  • Analyze AI workload characteristics including:
  • Training vs. inference workloads
  • GPU utilization patterns
  • Dynamic workload fluctuations
  • Rack-level power variability
  • Networking and latency requirements
  • Assess implications of AI workload behavior on infrastructure resiliency, scalability, efficiency, and operational design.
  • Develop technical recommendations and infrastructure strategies supporting future AI deployments.

AI Compute & Chip Architecture Evaluation

  • Analyze current and future AI compute platforms including NVIDIA GPU architectures, ARM-based platforms, custom AI accelerators and ASICs, optical networking and switching technologies, and emerging hyperscaler-designed AI chips.
  • Evaluate implications of evolving chip architectures on rack density, power consumption, cooling requirements, electrical distribution, mechanical infrastructure, space planning, and future development standards.
  • Model current and future AI rack power density trends including existing high-density deployments (50-120 kW), near-term AI deployments (150-300+ kW), and future ultra-dense AI cluster scenarios.
  • Assess long-term impacts of emerging chip architectures on energy efficiency and future data center design and development standards.

Data Center Design, Development & Construction

  • Support conceptual and detailed design efforts for AI-ready data center infrastructure.
  • Assist in developing long-term infrastructure roadmaps for high-density AI deployments, liquid cooling adoption, modular infrastructure strategies, utility coordination, grid-parallel and microgrid solutions, and future AI campus development.
  • Evaluate implications of AI infrastructure evolution on greenfield developments, existing facility retrofits, construction methodologies, scalability, and future campus master planning.
  • Collaborate with engineering, development, and construction teams to develop scalable AI-ready infrastructure standards and deployment models.

Energy Strategy & Power Infrastructure

  • Collaborate closely with the Energy Strategy Team to evaluate utility constraints, interconnection requirements, grid limitations, dynamic load fluctuation impacts, power quality and resiliency considerations, and onsite generation and distributed energy solutions.
  • Support analysis of grid-parallel and islanded microgrid architectures, fuel cells, Battery Energy Storage Systems (BESS), bridge power solutions, natural gas generation, and renewable integration opportunities.
  • Evaluate implications of AI workloads on substation development, transmission planning, utility coordination, and energy efficiency and PUE optimization.
  • Assess how future AI compute growth will influence utility planning and power infrastructure strategies.

Cooling & Thermal Management Technologies

  • Analyze current and emerging thermal management solutions including air cooling, direct-to-chip liquid cooling, immersion cooling, rear-door heat exchangers, and hybrid cooling architectures.
  • Assess implications of ultra-high-density AI deployments on mechanical system design, water usage, cooling scalability, heat rejection strategies, thermal resiliency, and future cooling infrastructure standards.
  • Evaluate cooling technologies and infrastructure requirements as AI rack densities continue to increase.

Vendor Engagement & Emerging Technology Assessment

  • Interface directly with technology vendors, OEMs, utilities, and strategic partners across power generation, UPS systems, electrical infrastructure, cooling technologies, liquid cooling platforms, AI compute infrastructure, and networking and optical interconnect technologies.
  • Lead technical assessments of next-generation technologies with respect to reliability, scalability, energy efficiency, sustainability, AI workload performance, construction complexity, and operational resiliency.
  • Support proof-of-concept initiatives, pilot deployments, and technology benchmarking efforts.
  • Develop executive-level recommendations regarding adoption of emerging AI infrastructure technologies and strategic engineering standards.

Cross-Functional Collaboration

  • Collaborate with design engineering, construction, operations, energy strategy, procurement, utilities, technology partners, and external engineering firms and consultants.
  • Support strategic planning initiatives and executive-level technical presentations.
  • Assist in developing future infrastructure standards and innovation roadmaps for AI-enabled data center platforms.
What makes you a good fit: (Qualifications)

Required

  • Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, Data Center Engineering, or a related technical discipline.
  • 5+ years of experience in one or more of the following: data center infrastructure, AI/HPC infrastructure, power systems engineering, cooling technologies, or advanced infrastructure engineering.
  • Strong understanding of emerging AI compute technologies and infrastructure implications.
  • Ability to analyze complex technical systems and translate findings into actionable engineering and infrastructure strategies.

Preferred

  • Master's degree and/or PhD in Engineering, Computer Science, Data Science, Energy Systems, or a related technical field.
  • Experience with hyperscale or colocation data center environments.
  • Knowledge of GPU infrastructure and AI workload behavior.
  • Familiarity with utility coordination and energy systems.
  • Understanding of high-density cooling technologies.
  • Experience supporting large-scale infrastructure development projects.
  • PE license or equivalent advanced technical credentials.

***Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or transfer sponsorship of an employment visa at this time, including CPT/OPT.***

NOTE: This job description is not intended to be all-inclusive. Employee may perform other related duties as assigned to meet the ongoing needs of the organization.

Cologix is proud to be an Equal Opportunity Employer. Qualified applicants are considered for employment without regard to age, race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or veteran status.  If you need assistance in applying for any of our open positions, please contact us at [email protected] or call 720-940-2551. 

The California Consumer Privacy Act ("CCPA") creates privacy rights relating to the collection, sale, disclosure, and deletion of consumers' personal information. The CCPA requires businesses to provide consumers, including job applicants and employees, with information about their rights, including a description of the categories of personal information to be collected and the purpose for which the information will be used. For additional information regarding your rights, including a description of the categories of personal information to be collected and the purpose for which the information will be used, please see https://cologix.com/privacy-policy/.

Cologix' data centers are ISO 27001:2022 and ISO 14001:2015 certified. These certifications demonstrate Cologix's commitment to both information security and environmental stewardship. At Cologix, protecting information assets and minimizing environmental impacts are everyone's responsibility.

Cologix employees are responsible for:
Understanding and following Cologix's information security, cybersecurity, privacy,
and environmental management policies, procedures, and standards.
Ensuring conformance with the requirements of both the Information Security
Management System (ISMS) and the Environmental Management System (EMS).
Remaining vigilant and reporting any information security or environmental incidents,
vulnerabilities, risks, or non-conformities to the appropriate teams.
Actively participating in Cologix's efforts to maintain and improve information security
and environmental performance.

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