Jobs at IntelliPro Group Inc.

Deliver and deploy Physical AI solutions across enterprise and public-facing environments. Develop applications, APIs, and integrations; integrate and troubleshoot hardware, networking, sensors, displays, and edge devices; conduct customer demonstrations; manage technical implementations and deployment timelines; and translate customer feedback into product improvements. The role requires cross-functional collaboration, hands-on troubleshooting, customer communication, and travel for deployments and industry events.

Build and scale high-volume robotics data infrastructure, including data processing, transformation, storage, validation, and delivery pipelines. Develop reliable distributed systems on AWS or GCP, handle large binary and multimodal datasets, and collaborate with customer engineering teams on customized solutions. The role requires strong backend engineering, production data pipeline ownership, cloud experience, and effective technical communication.

Design, develop, and maintain scalable backend services and APIs powering AI-driven customer engagement. Integrate AI models and LLM technologies, optimize systems for real-time performance and reliability, and collaborate with marketing, sales, and product teams. The role also involves evaluating emerging backend and AI technologies and delivering innovative solutions in a fast-paced startup environment.

Own end-to-end product design across human-AI interfaces, visual design, brand campaigns, motion, video, 3D assets, and interactive prototypes. Design touch and voice experiences, digital characters, product renders, launch materials, and web demos while partnering with engineering. The role requires strong visual craft, startup ownership, AI-assisted creative workflows, and the ability to maintain a cohesive brand across digital, physical, print, video, and 3D experiences.

Deploy and support physical AI agents at airports, stadiums, conferences, and other high-profile venues. Responsibilities include configuring hardware, sensors, networking, and edge compute; debugging on-site; writing Python and TypeScript software; integrating APIs; presenting demonstrations; and providing field insights to product and engineering teams.

Train, fine-tune, evaluate, and deploy generative video, audio, and multimodal models powering real-time AI avatars. Build large-scale data pipelines, optimize low-latency GPU inference, maintain distributed training infrastructure, define quality metrics, and collaborate with research, backend, and product teams to ship interactive avatar features.

Own the end-to-end customer experience for a hardware and software product, defining quality standards, identifying experience gaps, prioritizing roadmap fixes, and driving design and engineering delivery. Lead launch readiness, customer go-lives, field acceptance, monitoring, and post-launch improvements. Partner with customers, sales, deployment, customer success, founders, and engineering while using AI tools, logs, metrics, and field feedback to ensure polished product experiences.

Develop production-ready analog and mixed-signal layouts from floorplanning through physical verification. Collaborate with circuit designers and project teams to optimize matching, parasitics, noise isolation, reliability, area, and performance. Perform DRC and LVS using Cadence Virtuoso and Calibre, resolve issues, support layout reviews and production release, manage competing priorities, and improve layout methodologies. Memory-circuit layout experience and familiarity with memory interfaces or emerging non-volatile memory technologies are preferred.

Lead the architecture and technical direction of advanced graphics-oriented SoCs, including subsystem partitioning, interfaces, memory hierarchy, interconnect, cache coherency, performance modeling, and third-party IP integration. Collaborate across RTL, verification, physical design, firmware, software, and systems teams. Support validation, silicon bring-up, debugging, performance optimization, and long-term technology roadmaps.

Owns customer quality issues for a semiconductor company, including deviations, returns, failed samples, 8D reports, corrective actions, failure analysis, reliability testing, CAPA, and lot-hold decisions. Tracks customer quality metrics, coordinates cross-functional investigations, drives FMEA and process improvements, manages returned samples and evidence, and represents quality in customer reviews. Requires deep semiconductor manufacturing, testing, reliability, and quality-method expertise, plus strong English communication skills.

Build and scale AI-powered, user-facing web and multi-platform products. Own development from architecture through deployment and optimization, including real-time collaboration and interactive experiences. Integrate generative AI, LLMs, and AI workflows, while collaborating with product, design, and engineering teams. Drive technical decisions, improve engineering practices, lead technical projects, and mentor engineers.

Designs and delivers customer-facing AI solutions from discovery and proof of concept through deployment. Responsibilities include solution architecture, LLM/RAG/agent implementation, API and data pipeline integration, model deployment and monitoring, troubleshooting, technical training, and post-deployment support. The role evaluates business impact, coordinates cross-functional delivery, and helps establish implementation processes for scalable customer deployments.

Develop and manage relationships with U.S. AI data center power customers. Conduct customer visits, identify requirements, support technical discussions, RFQs, evaluations, design-ins, and project progression. Coordinate between customers and global R&D, product, FAE, and business teams. Research market and competitors, attend industry events, maintain opportunity pipelines, and track engagement metrics. The role is designed to develop an early-career professional into a key U.S. account and business development contributor.

Build and operate a financial cloud developer platform supporting independently versioned modules across global compliance sites. Responsibilities include CI/CD pipelines, reproducible builds, supply chain provenance, dependency graph and change impact tooling, GitOps deployment automation, Kubernetes controllers, site provisioning, version management, security patching, and test orchestration.

Build and ship production LLM-powered coding tools, internal AI products, multi-agent systems, and agentic workflows. Develop tool-calling, API orchestration, structured output, evaluation, benchmarking, and scalable Python backend systems. Evaluate models based on performance and cost, collaborate across product, security, and engineering teams, and independently deliver AI systems end to end.

Designs and evolves hyperscale internal platform infrastructure supporting build systems, dependency management, artifact registries, deployment workflows, API contracts, and monorepo governance. The role establishes reproducible builds, version compatibility, GitOps promotion, supply-chain security, artifact signing, and multi-region platform evolution for large engineering organizations.

Serves as the primary post-sales technical contact for enterprise customers, managing onboarding, installation, configuration, testing, deployment, training, and product adoption. Integrates robotic arms, teleoperation systems, and embodied AI platforms into customer workflows. Troubleshoots hardware, software, networking, and performance issues; coordinates resolutions with engineering teams; translates customer requirements into actionable feedback; and supports demonstrations, upgrades, field testing, proof-of-concept projects, and customer acceptance. Travel to customer sites is required as needed.

Lead executive compensation programs, Compensation Committee materials, executive pay decisions, benchmarking, proxy statement contributions, SEC disclosures, and governance compliance. The role supports compensation surveys and ensures executive rewards align with long-term shareholder value and investor expectations. This is a three-month hybrid contract in San Francisco with possible extension.

Leads complex technical programs for AI and robotics customers, translating research objectives into engineering requirements, project plans, milestones, and delivery processes. Coordinates research, engineering, hardware, data operations, and quality teams while managing scope, risks, resources, dependencies, and stakeholder communication. Oversees physical AI data-collection initiatives from solution design through execution, quality control, and final delivery, with emphasis on reliability, data quality, customer satisfaction, and scalable operating processes.

Prepare SOX control workbooks, review replacement deals and debook calculations, execute monthly NetSuite accounting activities, reconcile accounts, support revenue close validations, and document audit-ready work. The role requires accurate data analysis across NetSuite and Salesforce, journal entries, reconciliations, and knowledge of US GAAP and revenue accounting.