Assistant Vice President, AI Engineering

Role Overview

• You will lead operational delivery across AI Engineering: planning, staffing, execution, and shipment of projects
• You will translate strategy into executable technical plans, milestones, and resourcing models
• You will maintain visibility into project status, risks, dependencies, and delivery health
• You will guide execution practices across teams (planning cadences, estimation, delivery reviews, retrospectives, postmortems)
• You will ensure production readiness, on-call practices, and incident response processes are in place and improving
• You will lead long-term sustainability of AI systems post-launch, including maintenance, monitoring, and ongoing optimization
• You will be senior technical authority for AI Engineering and infrastructure decisions
• You will guide architecture for agentic AI systems, data platforms, evaluation frameworks, and production services
• with a focus on scalability, reliability, security, cost efficiency, and observability
• You will establish organizational standards for agent orchestration, memory, and tool use patterns
• You will lead cost governance for LLM-based systems (token economics, model selection tradeoffs)
• You will define evaluation strategy for LLM and agent-based systems, ensuring measurable performance criteria exist before production deployment
• You will partner with Staff and Principal Engineers across SNHU to establish and promote adherence to AI technical standards
• You will directly manage engineering and senior technical leads
• You will coach managers on delivery, performance, and team development
• You will lead staffing, hiring, onboarding and career growth
• You will foster a culture of accountability, psychological safety, and continuous improvement
• You will partner across SNHU teams, including AI Governance, Product, Data Science, Design, IT, and Academic partners to ensure smooth execution
• You will communicate delivery progress, tradeoffs, and constraints to senior leadership
• You will help translate technical realities into applicable decisions for senior leadership
• You will set expectations and create conditions for AI-augmented development across the organization: tooling decisions, workflow patterns, and evolving standards for how the team uses AI development tools

Requirements

• 10+ years of software engineering experience, with time in production systems
• 5+ years leading engineering teams through managers or senior technical leads
• Experience overseeing delivery for complex, multi-team technical projects
• Expertise balancing technical depth with people and operational leadership
• Experience in production software systems engineering
• Experience building and operating AI-enabled systems in production environments
• Experience with agentic AI architecture, LLM-based systems, and agent orchestration patterns
• Experience with cloud infrastructure (AWS, Azure, or equivalent), data pipelines, and system reliability
• Experience with evaluation methodologies for LLMs and agentic systems (offline evals, human-in-the-loop, production monitoring)
• Experience with AI development tools (GitHub Copilot, Cursor, Claude Code, or similar)
• Experience with complex architecture reviews, technical tradeoffs, and debugging when needed
• Experience establishing engineering processes that improve predictability without bureaucracy
• Familiarity with on-call models, incident response, and production operations
• Experience improving engineering quality, delivery speed, and system stability.

Tech Stack

• AWS
• Azure
• Cloud

Benefits

• High-quality, low-deductible medical insurance
• Low to no-cost dental and vision plans
• 5 weeks of paid time off (plus almost a dozen paid holidays)
• Employer-funded retirement
• Free tuition program
• Parental leave
• Mental health and wellbeing resources