Role Description
Reporting to our CEO, the Chief AI Officer will lead our AI transformation – own and drive our AI strategy, roadmap, and adoption.
What You’ll Be Doing:
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AI Strategy & Roadmap
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Own and drive the company-wide AI strategy, roadmap, and governance framework.
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Define the multi-year vision for AI adoption across service delivery, business development, and operations.
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Lead prioritization of AI initiatives against revenue, margin, and competitive differentiation outcomes.
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Report to the CEO on AI transformation progress; own the AI KPI scorecard.
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AI-Enabled Products & Services
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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.
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Lead productization of Fidus's engineering expertise into scalable, repeatable AI-augmented deliverables.
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Partner with discipline leads (FPGA, SI/PI, Layout, Software, Hardware, ASIC) to embed AI tooling into delivery workflows.
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Establish IP strategy around proprietary AI methods and tooling developed internally.
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AI Adoption & Change Management
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Drive measurable adoption of AI tools across all teams — engineering, operations, and business development.
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Design and execute a structured change management program: enablement, training, and accountability.
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Define and own adoption KPIs: cycle time reduction, AI-assisted delivery percentage, proposal and BD efficiency.
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Champion a culture of experimentation while maintaining rigorous quality standards in safety-critical engineering environments.
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Data Strategy & Infrastructure (in partnership with IT)
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Partner with IT to define and evolve Fidus's data architecture, governance, and quality standards as the foundation for AI capability.
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Collaborate with IT to build and maintain the data platform required to support AI model development, training, and deployment.
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Partner with IT and Legal to ensure data practices meet compliance requirements including ITAR, export control, and client NDA obligations.
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Work closely with IT and engineering leadership to instrument delivery processes for systematic data capture and to maintain data quality at the source.
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Client-Facing AI Leadership
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Serve as Fidus's external AI authority — engaging clients, strategic partners, and industry forums.
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Advise clients on AI integration into their hardware, firmware, and systems product development programs.
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Support channel and business development by articulating Fidus's AI differentiation to silicon vendors, EDA partners, and the broader partner ecosystem.
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Build & Lead the AI Organization
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Hire, develop, and manage the AI function — engineers, data scientists, and ML operations.
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Define the organizational model: centralized Center of Excellence or embedded discipline-level AI leads.
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Manage AI vendor and tool relationships — model providers, MLOps platforms, and data tooling — in coordination with IT procurement and security standards.
Qualifications
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Proven track record of driving AI adoption and transformation inside a services or professional services organization.
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10+ years in technology leadership; 3+ years in a senior AI/ML leadership role with demonstrated organizational impact.
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Hands-on expertise in data architecture, data governance, and ML pipeline development.
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Demonstrated experience building AI-enabled products or productized service offerings, from ideation through commercialization.
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History of executing on strategic roadmaps under ambiguity with measurable business outcomes.
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Able to translate AI strategy into board-level narrative and into day-to-day engineering direction.
Requirements
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Strong preference for background in engineering services, EDA, semiconductor, or adjacent deep-tech industries.
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Familiarity with safety-critical or regulated engineering environments: A&D, medical, automotive.
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Experience in ITAR or export-controlled data environments.
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Prior experience in a company undergoing strategic transformation — high-growth, PE-backed, or M&A integration.
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Hands-on experience with LLMs, agentic AI frameworks, or AI applied to CAD/EDA and hardware design workflows.
Benefits
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Collaborative work environment focused on openness, trust, and shared ownership.
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Encouragement to contribute ideas and learn from one another.
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Meaningful impact through the work done.
