Attain Talent - VP, Technology & AI Strategy
Requirements
• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related field • 12+ years in software engineering, architecture, platform delivery, or technology leadership • 5+ years in a senior leadership role such as Director, VP, or Principal Architect • Experience leading enterprise-scale platform or SaaS development • Strong cloud architecture experience in AWS, Azure, or GCP • Demonstrated success introducing automation, AI, or process transformation into engineering or delivery environments • Experience delivering solutions to state or local government clients • Experience with AI-enabled products, data-intensive platforms, or intelligent workflow systems • Experience operationalizing AI in internal business processes, not just engineering workflows • Experience commercializing emerging technology into product features or service offerings • Familiarity with AI governance, risk controls, and human-in-the-loop operating models • Experience in milestone-based, contract-driven delivery environments • What Success Looks Like in the First 12–18 Months • Engineering execution is more disciplined, predictable, and • The platform is more scalable, reusable, and architecturally • AI is embedded in key internal workflows in ways that measurably reduce manual effort, improve quality, and increase speed. • Cardinality has a defined AI governance model and a practical company-wide approach to • AI-enabled capabilities are being shaped into differentiated offerings with clear commercial • The engineering leadership team is stronger, more scalable, and better aligned to company growth
Responsibilities
• Lead the engineering organization responsible for platform development and client • Oversee technical execution from solution design through deployment, transition, and operational • Establish strong delivery discipline across planning, SDLC governance, release management, documentation, operational readiness, and quality assurance. • Provide portfolio-level oversight across multiple engagements to improve predictability, consistency, and resource efficiency. • Evolve the platform architecture to support enterprise-scale deployments, configurability, maintainability, and multi-client reuse. • Define and enforce technical standards across integrations, data flows, security, deployment models, and performance. • Convert implementation-specific solutions into reusable platform capabilities, accelerators, and packaged offerings. • Define and lead the company’s practical AI strategy across engineering, delivery, QA, support, documentation, and shared services. • Operationalize AI through repeatable workflows, tooling standards, governance controls, human review practices, and measurable KPIs. • Establish policies for responsible AI usage covering data handling, validation, auditability, and secure • Partner with product, sales, and executive leadership to identify AI-enabled features, accelerators, and service offerings that can be commercialized. • Translate client and market needs into practical AI use cases such as intelligent search, document processing, summarization, workflow augmentation, and decision support. • Support positioning, roadmap definition, and technical value articulation for AI-enabled • Oversee cloud infrastructure, DevOps practices, deployment automation, and operational • Build and mentor a high-performing leadership bench of engineering managers, architects, and technical leads. • Upskill teams on effective AI usage and improve collaboration across distributed and international • Serve as the senior technical leader for RFPs, proposals, solution shaping, and client technical • Translate procurement requirements into executable architectures, realistic estimates, and delivery • Build trust with government stakeholders through disciplined execution, transparency, and sound technical judgment.
Benefits
• $200,000—$225,000 USD
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