Vice President - AI Engineering
First seen by Alion on Sep 9, 2026.
Role Overview:
We're looking for a Vice President of AI Engineering to lead our AI organization into its next phase of scale and impact. This is a high-ownership role for a technically deep, customer-obsessed leader who thrives in a fast-moving startup environment and wants to own both strategy and execution across our most critical AI products.
What You'll Own:
- Jointly define, communicate, and drive the company-wide AI vision, strategy, and technical roadmap.
- Provide high-level technical architecture guidance and thought leadership across all AI platforms and products.
- Act as the primary AI spokesperson in strategic customer and partner discussions.
- Own full end-to-end accountability for a major product portfolio, covering vision, roadmap, prioritization, delivery, quality, and customer adoption.
- Lead and own all forward deployment engineering activities for the AI product suite.
- Partner closely with other product leaders to eliminate duplication and accelerate delivery.
- Provide visible leadership, mentoring, and coaching to the broader AI organization.
- Apply strong project management discipline to ensure on-time, high-quality delivery of complex AI initiatives.
What Success Looks Like:
- Architect and deliver production-grade AI systems that achieve industry-leading standards in scalability, reliability, latency, and cost efficiency.
- Drive technical excellence across the engineering organization through agentic SDLC.
- Build and scale high-performing AI engineering teams that consistently ship complex, high-impact features on time.
- Deliver measurable business impact through your product portfolio.
Qualifications:
- 10+ years of progressive software engineering experience with at least 5+ years leading large-scale AI/ML organizations.
- Deep hands-on expertise in modern AI/ML technologies, including large language models, computer vision, MLOps pipelines, model optimization, distributed training, and high-performance inference infrastructure.
- Proven track record of architecting and shipping complex, reliable AI products.
- Experience in forward deployment engineering, including technical pre-sales and solution architecture.
- Demonstrated success building, mentoring, and scaling high-performing AI engineering teams (50+ engineers).
- Expertise in cloud-native platforms (AWS, GCP, or Azure), distributed systems, CI/CD pipelines, and infrastructure-as-code.
- Startup mindset with comfort operating in ambiguity, high ownership, and a bias toward measurable business impact.
Skills
Artificial Intelligence, Machine Learning, Generative AI, AI Product Development, AI Project Management