Chief AI Officer

🔥 3 hours ago

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Fidus Systems

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2001

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Fidus Systems is a company that provides comprehensive electronic and hardware design services to electronics manufacturers. They specialize in FPGA design, ASIC design, verification, and validation, with capabilities in embedded software, hardware, PCB layout, signal and power integrity, and mechanical and thermal design. Fidus Systems is skilled in working with leading technologies like AMD and Intel, transforming concepts into high-reliability products for high-demand industries such as aerospace, telecommunications, medical devices, and consumer electronics. The company is known for helping clients accelerate complex designs through its expert capabilities and flexible engagement models.

📋 Description

• Own and drive the company-wide AI strategy, roadmap, and governance framework • Define the multi-year vision for AI adoption across service delivery, business development, and operations • Lead prioritization of AI initiatives against revenue, margin, and competitive differentiation outcomes • Report to the CEO on AI transformation progress; own the AI KPI scorecard • Collaborate with CTO and Delivery Leaders to identify and build net-new AI-enabled service offerings that expand Fidus's addressable market — e.g., AI-assisted SI/PI analysis, automated design review, embedded AI in customer product development • Lead productization of Fidus's engineering expertise into scalable, repeatable AI-augmented deliverables • Partner with discipline leads (FPGA, SI/PI, Layout, Software, Hardware, ASIC) to embed AI tooling into delivery workflows • Establish IP strategy around proprietary AI methods and tooling developed internally • Drive measurable adoption of AI tools across all teams — engineering, operations, and business development • Design and execute a structured change management program: enablement, training, and accountability • Define and own adoption KPIs: cycle time reduction, AI-assisted delivery percentage, proposal and BD efficiency • Champion a culture of experimentation while maintaining rigorous quality standards in safety-critical engineering environments • Partner with IT to define and evolve Fidus's data architecture, governance, and quality standards as the foundation for AI capability • Collaborate with IT to build and maintain the data platform required to support AI model development, training, and deployment • Partner with IT and Legal to ensure data practices meet compliance requirements including ITAR, export control, and client NDA obligations • Work closely with IT and engineering leadership to instrument delivery processes for systematic data capture and to maintain data quality at the source • Serve as Fidus's external AI authority — engaging clients, strategic partners, and industry forums • Advise clients on AI integration into their hardware, firmware, and systems product development programs • Support channel and business development by articulating Fidus's AI differentiation to silicon vendors, EDA partners, and the broader partner ecosystem • Hire, develop, and manage the AI function — engineers, data scientists, and ML operations • Define the organizational model: centralized Center of Excellence or embedded discipline-level AI leads • Manage AI vendor and tool relationships — model providers, MLOps platforms, and data tooling — in coordination with IT procurement and security standards

🎯 Requirements

• Services industry experience: Proven track record of driving AI adoption and transformation inside a services or professional services organization — not a product company. You understand the utilization model, the people dynamics of a billable delivery environment, and how to drive change without disrupting client commitments. • AI transformation leadership: 10+ years in technology leadership; 3+ years in a senior AI/ML leadership role with demonstrated organizational impact. You have taken AI from concept to deployed, production-grade capability in an organization that did not start AI-native. • Deep data background: Hands-on expertise in data architecture, data governance, and ML pipeline development. Skilled at working across functional boundaries — able to engage credibly with both engineers and IT leadership, not just manage upward. • Product development experience: Demonstrated experience building AI-enabled products or productized service offerings, from ideation through commercialization. • Execution track record: History of executing on strategic roadmaps under ambiguity with measurable business outcomes — revenue, margin, efficiency. You ship. • Executive communication: Able to translate AI strategy into board-level narrative and into day-to-day engineering direction. Equally fluent in both registers. • Strong Preference • Background in engineering services, EDA, semiconductor, or adjacent deep-tech industries • Familiarity with safety-critical or regulated engineering environments: A&D, medical, automotive • Experience in ITAR or export-controlled data environments • Prior experience in a company undergoing strategic transformation — high-growth, PE-backed, or M&A integration • Hands-on experience with LLMs, agentic AI frameworks, or AI applied to CAD/EDA and hardware design workflows.