Full-Time
Principal AI Infrastructure Engineer
Analog Devices
10,001+ employees
Designs high-performance analog and DSP ICs
Compensation Overview
$200k - $275k/yr
No H1B Sponsorship
Burlington, MA, USA
In Person
US Citizenship Required
 DevOps & Infrastructure (2) |
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- Recognized expert in AI infrastructure with deep knowledge of on-premises, hybrid, and cloud-native architectures, with demonstrated influence and impact across organizations or business units.
- Proven track record of architecting infrastructure systems that serve multiple, sometimes competing, organizational needs while maintaining coherence and simplicity.
- Expert communication and strategic thinking skills—ability to translate technical architecture into research and product impact.
- Expert-level proficiency with Kubernetes, distributed compute frameworks (Ray, Spark, or equivalent), and the ability to define org-wide orchestration and scheduling strategies.
- Mastery of Infrastructure-as-Code and GitOps frameworks, with demonstrated ability to design reusable, multi-team infrastructure patterns and platforms.
- Deep expertise in GPU and accelerator resource management, cost optimization, and performance tuning across diverse workload types and hardware configurations.
- Expert knowledge of cloud platforms (Amazon Web Services, Microsoft Azure, or equivalent) and proven ability to architect multi-cloud or hybrid strategies that balance flexibility, cost, and operational complexity.
- Strong background in distributed systems design, including handling scale, reliability, consistency, and failure modes across heterogeneous infrastructure.
- Demonstrated ability to lead large, cross-team initiatives from conception through execution, influencing complex decision-making and shaping long-range technical directions.
- Strong mentoring orientation with demonstrated success developing leaders and upskilling teams across the organization in infrastructure and platform topics.
- Recognized ability to drive innovation, anticipate organizational needs, and architect durable solutions that scale with the business.
- Help define and evolve the organizational vision for AI developer experience, identifying gaps and opportunities across the full AI development lifecycle and across all deployment environments.
- Lead cross-team initiatives that systematically improve how AI builders experience infrastructure—from experimentation through production—creating measurable improvements in developer productivity and satisfaction.
- Work strategically with data science teams, and research groups to understand emerging AI use cases and infrastructure needs at the frontier of the organization's work.
- Establish org-wide patterns, standards, and best practices for AI infrastructure that are adopted across multiple business units and geographies.
- Design and advocate for developer-first abstractions and platforms that absorb infrastructure complexity while enabling advanced customization for specialized use cases.
- Help evolve governance frameworks—including model versioning, experiment tracking, deployment workflows, and compliance standards—that scale with organizational growth without stifling innovation.
- Shape the organizational approach to infrastructure cost, performance, and reliability trade-offs, ensuring alignment with business objectives across teams.
- Mentor and develop engineers across the organization, creating a culture of architectural excellence and infrastructure craftsmanship.
- Architect the organization's long-term AI infrastructure strategy spanning on-premise, hybrid, and cloud-native environments, ensuring cohesive developer experience across all.
- Define reference architectures and technical standards for compute orchestration, model serving, inference optimization, and resource management that guide platform development across teams.
- Lead the design of scalable, multi-region AI infrastructure that supports ADI's geographic expansion and business unit diversity, accounting for regulatory, latency, and cost requirements.
- Own infrastructure innovation initiatives that improve efficiency, reduce cost, and unlock new capabilities—including GPU utilization optimization, heterogeneous compute strategies (CPUs, GPUs, NPUs, FPGAs), and emerging accelerator technologies.
- Establish enterprise-level observability, governance, and security frameworks for AI infrastructure that maintain compliance across diverse environments while enabling rapid iteration.
- Drive architectural decisions on critical infrastructure dependencies (Kubernetes strategies, container runtimes, distributed compute frameworks, model serving platforms, etc.), influencing multi-year technical roadmaps.
- Partner with infrastructure and cloud teams to evolve shared platforms and services that serve AI workloads, ensuring architectural alignment across the organization.
- Anticipate infrastructure, architectural, and organizational risks—from evolving workload patterns to regulatory changes to emerging security threats—and implement durable solutions adopted org-wide.
- Lead by example in creating reusable Infrastructure-as-Code frameworks, architectural patterns, and tooling that amplify team productivity and reduce toil across the organization.
- Deep expertise in building or scaling AI infrastructure for robotics, autonomous systems, or industrial perception at enterprise scale, with demonstrated patterns and reusable frameworks.
- Expert-level knowledge of ROS/ROS2 ecosystems and the infrastructure challenges of deploying and managing ML models across diverse robotic platforms and environments.
- Strategic experience with edge AI deployment and the architectural tradeoffs between centralized cloud inference, edge inference, and hybrid models in physical systems.
- Background designing ML infrastructure that supports rapid adaptation, few-shot learning, and task transfer in physical systems, enabling scalable deployment across heterogeneous environments.
- Deep understanding of heterogeneous compute architectures (CPUs, GPUs, TPUs, NPUs, FPGAs) and experience optimizing inference pipelines for specialized hardware.
- Experience with real-time operating systems and the infrastructure requirements of hard real-time, safety-critical AI systems.
- Strategic familiarity with manufacturing, autonomous vehicles, or healthcare domains and the business and technical requirements that shape AI infrastructure in those industries.
- Demonstrated ability to influence robotics, manufacturing, or autonomous systems teams and shape architectural decisions that bridge domain expertise with modern AI/ML capabilities.
- Track record of translating specific domain engagements into generalizable, org-wide AI infrastructure capabilities and standards.
ADI designs, manufactures, and sells high-performance analog, mixed-signal, and DSP integrated circuits that sense, measure, interpret, connect, and power the physical world in electronic devices. Its products include data converters, amplifiers, and power-management ICs that OEMs embed to handle analog sensing and digital processing inside their products. ADI differentiates itself through a broad, industry-spanning portfolio and close collaboration with customers to solve complex engineering challenges, rather than focusing on a single product type. Its goal is to provide reliable signal-processing solutions that bridge the physical world and digital systems, helping customers create more capable electronic products.
Company Size
10,001+
Company Stage
IPO
Headquarters
Wilmington, Massachusetts
Founded
1965
Simplify's Take
What believers are saying
- Nine consecutive quarters above-seasonal ATE growth driven by AI infrastructure capital spending.
- Industrial robotics partnerships with Nvidia, TI, Infineon position ADI for ecosystem capture.
- Gross margin expansion to 74% and 11% dividend increase signal strong cash generation.
What critics are saying
- Texas Instruments undercuts ADI pricing in industrial and automotive analog markets.
- Nvidia dependency relegates ADI to secondary supplier role in AI robotics platforms.
- US export controls on RF and DSP ICs halt 20-30% communications revenue.
What makes Analog Devices unique
- Thailand LEED Platinum facility strengthens Asia-Pacific test and packaging capacity resilience.
- Project SPECTRA RF-to-GPU integration positions ADI for edge AI signal processing.
- Strategic Sense investment expands ADI into grid edge intelligence and smart utilities.
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Company News
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Analog Devices has opened a new advanced manufacturing facility in Thailand, strengthening its global test and packaging capacity in the Asia-Pacific region. The facility, located in Thailand's Eastern Economic Corridor, supports the company's hybrid manufacturing strategy combining internal factories and external partners. The site enhances Analog Devices Thailand's backend manufacturing capabilities, adding cleanroom capacity for test operations, wafer-level processing and chip scale packaging. The facility serves industrial, automotive, communications, consumer and digital healthcare markets. Built to LEED Platinum standards, the facility is the first in ADI's network pursuing this certification. It features energy-efficient systems, water recycling and is Thailand's first semiconductor manufacturer using low-carbon liquid nitrogen. The expansion supports ADI's commitment to 100% renewable electricity whilst developing Thailand's semiconductor talent through university partnerships and training programmes.
Nvidia partners with chipmakers to advance industrial robotics. Jay Liu, Taipei Mar 18, 2026, 16:06 0 Credit: DIGITIMES At Nvidia's GTC 2026 conference, major chipmakers - including Texas Instruments (TI), Infineon Technologies AG, NXP Semiconductors, Analog Devices (ADI), and Synopsys - announced new collaborations centered on robotics built around Nvidia's... MEMBERSHIP BENEFITS * Full access to articles dating back to 2000. * Real-time access to the news as it breaks. * Access to premium content. * Full access to Tomorrow's Headlines. * Asia Supply Chain 250 dataset access.
Analog Devices has announced plans to increase gross margins from 71% to 74% and add 200 basis points to operating margins in fiscal Q2, whilst highlighting nine consecutive quarters of above-seasonal performance in automatic test equipment (ATE), aerospace and automotive. Speaking at Morgan Stanley's Technology, Media & Telecom Conference in early March 2026, management emphasised that rising AI capital spending could significantly boost its ATE business, linking AI infrastructure expansion to demand for its test and measurement solutions. The company raised its dividend by 11% to $1.10 per share in February 2026, demonstrating confidence in cash generation alongside margin targets. However, investors face risks from potential margin pressure if competition or macroeconomic conditions weaken demand. The narrative projects $14.3 billion revenue by 2028, requiring 11.3% yearly growth.
Powering the future of RF intelligence: the Project SPECTRA joint effort. March 11, 2026 - Wolf Advanced Technology (WOLF) is proud to announce a joint live demonstration at NVIDIA GTC 2026 with Analog Devices, Inc. (ADI) and Voyager Technologies(NYSE: VOYG). For the first time, WOLF Advanced Technology Inc. is introducing Project SPECTRA - a SOSA-aligned, rugged VPX platform that integrates AI acceleration, high-performance embedded computing, and advanced RF signal processing within a 350 W envelope for extreme-edge environments. At the heart of the system is WOLF's 153W (VPX3U-AD5000E-CX7-OPTICAL), powered by the NVIDIA RTX(TM) 5000E embedded GPU and ConnectX(R)-7 SmartNIC, enabling high-bandwidth optical connectivity and low-latency GPUDirect RDMA data movement directly into GPU memory. ADI's ADSY1100 delivers precision RF acquisition and FPGA processing, streaming data over dual 100G optical links for real-time GPU acceleration. Voyager Technologies' NVIDIA Holoscan-based software orchestrates system control and presents a live performance dashboard, demonstrating seamless RF-to-GPU data flow across an open, modular architecture. Integrated in a SOSA-aligned 3U VPX chassis with system control provided by a Concurrent Hermes SBC, Project SPECTRA highlights how industry leaders can combine open standards, optical fabric, and accelerated computing to redefine intelligent signal processing at the edge. Join WOLF, ADI, and Voyager Technologies at NVIDIA GTC 2026 to experience Project SPECTRA live. Visit Booth 3306 to engage with its engineering teams, explore the architecture in detail, and see firsthand how accelerated RF processing and AI-driven analytics are redefining performance at the extreme edge. Event details. Event: NVIDIA GTC 2026 Dates: March 16-19 Booth: 3306 Location: San Jose McEnery Convention Center About Wolf Advanced Technology Wolf Advanced Technology (WOLF) delivers rugged, high-performance embedded computing, AI, and video processing solutions for aerospace and defense. Leveraging NVIDIA(R) GPUs and AMD(R)/Xilinx(R) FPGAs, WOLF delivers SWaP-optimized SOSA(R) aligned VPX, XMC, MXM/MXC, VNX+, SFF, and custom solutions, enabling real-time video, AI inference, and high-speed data in mission-critical environments. About Analog Devices Analog Devices (ADI) is a global semiconductor leader empowering the Intelligent Edge. Through its portfolio of analog and mixed-signal technologies, RF solutions, power management, processors, and sensors, ADI transforms real-world signals into actionable insights, helping customers reduce complexity, accelerate innovation, and enable smarter, more connected systems across diverse industries. About Voyager Technologies Voyager Technologies is a defense and space technology company committed to advancing and delivering transformative, mission-critical solutions. By tackling the most complex challenges, Voyager aims to unlock new frontiers for human progress, fortify national security, and protect critical assets from ground to space. For more information visit: voyagertechnologies.com and follow on LinkedIn and X.