[Hiring] Lead Solution Architect @World Wide Technology

Role Description

The Lead Solution Architect, Physical AI is the technical owner of WWT's Physical AI engagements, accountable for the design and delivery of systems that perceive the physical world through cameras and sensors, understand what is happening and act on it through people, workflows, machines, and robots. The work spans computer vision, digital twin, and robotics, with perception as the foundation for all of it. This role scopes the first phase of each engagement with the account team, selects the platform and reference architecture, and ensures the customer's data, labels, and model weights remain portable regardless of platform, so WWT is always the architect of record no matter who builds each piece. The role requires deep experience taking computer vision and machine learning systems from pilot to production in real operating environments, where lighting, weather, camera conditions, and network behavior differ from the demo, along with the judgment to set technical standards other engineers follow. The Lead Solution Architect works alongside engineers, collaborates with product and account leadership on platform evaluations and engagement standards, and sets the technical direction for Physical AI engineers as the team grows.

Qualifications

• 10+ years of experience in customer engagement, solution design, or technology delivery, with 3 - 5 years of leadership experience
• Ability to communicate and collaborate with senior client leaders, as well as internal WWT team members, driving towards a strategic solution
• Demonstrated ability to drive innovation and conceive creative solutions to intricate or ambiguous problems within collaborative team settings
• Technical mastery of one or more key domains
• Team leadership skills, ability to orchestrate teams in developing multiple solutions
• Production computer vision: hands-on depth across detection, segmentation and tracking, video analytics on streaming and recorded footage, and working knowledge of vision language model approaches
• Visual data quality: understands that model performance is bounded by what the sensor delivers, and designs for lighting, weather, lens contamination, compression and dropped frames from the first architecture review, not after the pilot breaks
• Edge deployment: experience deploying inference on NVIDIA Jetson or on-prem GPU hardware, including model optimization (ONNX, TensorRT), containerization and the tradeoffs between edge, on-prem and cloud inference
• Video and camera integration: comfortable with RTSP and ONVIF, GStreamer or equivalent pipelines, and integrating with commercial video management systems and existing camera estates
• Platform fluency: working experience with at least one commercial vision AI or machine learning platform covering data curation, labeling, training, deployment and monitoring, and a point of view on where these platforms help and where they get in the way
• Enterprise integration: experience connecting vision outputs to the systems a plant, utility or venue already runs on (MES, SCADA, historians, work-order or incident tools) and alerting through the channels operators actually watch
• Scoping and estimation: has written the technical portion of a statement of work, sized the effort, and been accountable when the estimate was wrong
• Customer presence: able to hold the room with a plant manager, a director of digital technology and a CIO in the same week, and translate between them without overclaiming
• Autonomy: comfortable being the first architect on a new team, with ambiguity about tools, process and org structure, and able to set standards others follow
• Preferred: NVIDIA stack (DeepStream, Metropolis microservices, Triton, Isaac or Omniverse)
• Preferred: digital twin and simulation familiarity (Omniverse, Unity or Unreal) sufficient to collaborate where vision and simulation converge
• Preferred: domain exposure in manufacturing quality or throughput, utility field and vegetation operations, or venue and stadium operations
• Preferred: LiDAR and 3D point cloud processing and spatial reasoning
• Preferred: Robotics integration experience (ROS 2, AMR or robot arm platforms, robot perception)
• Preferred: prior work inside a technology partner program or co-sell motion, including resell versus referral economics

Requirements

• Owns the end-to-end technical design for each Physical AI engagement, from camera and sensor ingest through labeling, training, deployment, alerting and monitoring, and, as engagements mature, simulation and robot integration
• Partners with the account team to scope the first phase of an engagement, confirming the sponsor, the measurable outcome, camera and data readiness, and a clear path to a repeatable offer
• Writes the technical sections of the statement of work and estimates the effort
• Chooses the platform and reference architecture for each engagement from WWT's partner portfolio and documents why
• Escalates when the fit is wrong
• Designs so the customer's data, annotations and model weights can leave any platform WWT uses
• Specifies export formats, model formats such as ONNX and TensorRT, and the handoff artifacts WWT delivers at the end of each phase
• Runs structured evaluations of candidate platforms with the Product Director: defines the test dataset and scoring dimensions, executes the trials in the ATC and writes the recommendation
• Specifies the inference footprint (NVIDIA Jetson, on-prem GPU or cloud), the video pipeline, and the integration with the customer's cameras, video management systems and operational systems
• Sets the engineering standards the Forward Deployed Engineers build to, reviews their designs and code, and unblocks them on site
• Owns the reusable reference architectures and templates the team carries into each new engagement
• Acts as the technical counterpart to partner solution engineers on active accounts
• Feeds production findings back to partners and tracks what they fix
• Defines what done looks like at the end of a pilot including runbooks, monitoring, retraining triggers and the operating model the customer or WWT managed services takes over
• Turns each engagement into something WWT can repeat with reference architectures, estimating models, demo assets in the ATC and AI Proving Ground, and input to which offers WWT invests in next

Benefits

• Health and Wellbeing: Health (Medical & Prescription), Dental, and Vision Care, Onsite Health Centers (MO & IL), Employee Assistance Program, Wellness program
• Financial Benefits: Competitive Pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Flexible Spending Accounts, Tuition Reimbursement
• Paid Time Off: PTO & Holidays, Parental Leave, Medical Leave, Military Leave, Bereavement, Day of Caring
• Additional Perks: Family Planning Benefits, Nursing Mothers Benefits, Voluntary Legal, Voluntary Supplemental Accident/Illness/Hospital, Voluntary ID Theft, Pet Insurance, Employee Discount Program