VP, Technology & AI Strategy

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. &l