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.
  • 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