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VP, Technology & AI Strategy
attaintalent • United States - Remote
Posted: April 14, 2026
Job Description
Role Overview
A client of Attain Talent is seeking a senior technology executive to lead engineering execution, platform delivery, architecture, and AI strategy across the organization. This leader will build a disciplined, high-performing technology function capable of delivering complex government programs while advancing the company’s platform, operational maturity, and AI-enabled growth agenda.
The role sits at the intersection of engineering leadership, platform architecture, DevOps, client delivery, productization, and technical support for growth. A core mandate is to operationalize AI internally across engineering, QA, support, documentation, and delivery while also shaping AI-enabled capabilities that can be commercialized in the market.
Internal AI Operationalization
- Embed AI into internal workflows to reduce manual effort, improve quality, and increase delivery consistency.
- Convert AI-enabled capabilities into differentiated features, accelerators, and service offerings.
AI Commercialization
- Partner with product and sales to identify marketable AI use cases suited to government environments.
- Ensure offerings are explainable, secure, supportable, and tied to real client value.
Key Responsibilities
- Engineering Execution & Delivery Leadership
- 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.
- Platform Architecture & Productization
- 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.
- AI Strategy, Operationalization & Governance
- 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
- AI Commercialization & Market Differentiation
- 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
- Infrastructure, DevOps & Leadership
- 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
- Business Development & Client Engagement
- 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.
Required Qualifications
- 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
Preferred Qualifications
- 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
Additional Information
Our client offers a comprehensive benefits package designed to support employees’ health, financial well‑being, and time away from work. Benefits for eligible employees include medical, dental, and vision coverage with employer cost‑sharing; company‑paid life and disability insurance; a 401(k) plan with a 3% safe harbor employer contribution that is fully vested; generous paid time off that increases with tenure; and paid company holidays.
Additional Content
Role Overview
A client of Attain Talent is seeking a senior technology executive to lead engineering execution, platform delivery, architecture, and AI strategy across the organization. This leader will build a disciplined, high-performing technology function capable of delivering complex government programs while advancing the company’s platform, operational maturity, and AI-enabled growth agenda.
The role sits at the intersection of engineering leadership, platform architecture, DevOps, client delivery, productization, and technical support for growth. A core mandate is to operationalize AI internally across engineering, QA, support, documentation, and delivery while also shaping AI-enabled capabilities that can be commercialized in the market.
Internal AI Operationalization
- Embed AI into internal workflows to reduce manual effort, improve quality, and increase delivery consistency.
- Convert AI-enabled capabilities into differentiated features, accelerators, and service offerings.
AI Commercialization
- Partner with product and sales to identify marketable AI use cases suited to government environments.
- Ensure offerings are explainable, secure, supportable, and tied to real client value.
Key Responsibilities
- Engineering Execution & Delivery Leadership
- 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.
- Platform Architecture & Productization
- 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.
- AI Strategy, Operationalization & Governance
- 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
- AI Commercialization & Market Differentiation
- 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
- Infrastructure, DevOps & Leadership
- 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
- Business Development & Client Engagement
- 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.
Required Qualifications
- 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
Preferred Qualifications
- 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
Additional Information
Our client offers a comprehensive benefits package designed to support employees’ health, financial well‑being, and time away from work. Benefits for eligible employees include medical, dental, and vision coverage with employer cost‑sharing; company‑paid life and disability insurance; a 401(k) plan with a 3% safe harbor employer contribution that is fully vested; generous paid time off that increases with tenure; and paid company holidays.